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Global epidemiology of non-typhoidal Salmonella infections in humans

Hendriksen, Rene S.; Aarestrup, Frank Møller; Wegener, Henrik Caspar

Publication date:2010

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Citation (APA):Hendriksen, R. S., Aarestrup, F. M., & Wegener, H. C. (2010). Global epidemiology of non-typhoidal Salmonellainfections in humans. Kgs. Lyngby, Denmark: Technical University of Denmark (DTU).

http://orbit.dtu.dk/en/publications/global-epidemiology-of-nontyphoidal-salmonella-infections-in-humans(19407bbd-a889-453d-aa29-1849c1e27fa1).html

René HendriksenPhD ThesisJanuary 2010

Global epidemiology of non-typhoidal Salmonella infections in humans

National Food Institute

Technical University of Denmark

Mørkhøj Bygade 19

DK-2860 Søborg

Tel +45 35 88 70 00

Fax +45 35 88 70 01

www.food.dtu.dk

ISBN: 978-87-92158-61-1

SUPERVISORS AND FUNDING The research has been conducted entirely at the National Food Institute, Technical University of

Denmark in collaboration with 29 co-authors from 15 research institutes in ten countries;

Denmark, the United States, Switzerland, Thailand, Austria, Ireland, the Netherlands, England,

France, and South Korea. The work was supported by a grant 274-05-0117 from the Danish

Research Agency and the World Health Organization Global Salm-Surv

(www.who.int/salmsurv).

Supervisors:

� Institute Director, PhD, Henrik Caspar Wegener, National Food Institute, -Technical

University of Denmark, Denmark.

� Professor, PhD, Frank Møller Aarestrup, Division of Microbiology and Risk Assessment,

National Food Institute, Technical University of Denmark, Denmark.

Assessment Committee:

� Professor, PhD, Jaap Wagenaar, Department of Infectious Diseases and Immunology,

Faculty of Veterinary Medicine, Utrecht University and Central Veterinary Institute of

Wageningen UR, The Netherlands.

� Head of Division, PhD, Bjarke Bak Christensen, Division of Microbiology and Risk

Assessment, National Food Institute, Technical University of Denmark, Denmark.

� Director, PhD, Jørgen Schlundt, Department of Food Safety and Zoonoses, World Health

Organization, Switzerland.

Front-page designed by Susanne Carlsson, National Food Institute, Technical University of

Denmark, Copenhagen, Denmark.

Printed by Schultz Grafisk, Albertslund, Denmark.

ISBN : 978-87-92158-61-1

i

LIST OF CONTENT SUPERVISORS AND FUNDING..................................................................................................i

ACKNOWLEDGEMENTS..........................................................................................................iv

LIST OF ORIGINAL ARTICLES ...............................................................................................v

RESUMÉ...................................................................................................................................... vii

SUMMARY.....................................................................................................................................x

BACKGROUND, PURPOSE AND RESEARCH APPROACH ........................................... xiii

INTRODUCTION ..........................................................................................................................1

GLOBAL DISTRIBUTION OF SEROVARS AND TRENDS IN HUMANS..........................2

HUMAN EPIDEMIOLOGY .........................................................................................................7

�� .....................................................................7

�� ..................................................................................................9

�� ......................................................................................................10

�� ..............................................................11

MAIN RESERVOIRS..................................................................................................................13

�� .................................................................................14

�� .........................................................................................................15

TRANSMISSION – LOCAL AND GLOBAL ...........................................................................20

�� ..................................................................................................20

�� .......................................................................................................................22

� �� ....................................................................................23

� �� ....................................................................................................................24

� �� ..............................................................................................................25

SURVEILLANCE ........................................................................................................................27

�� ................................................................................................................................27

�� ..................................................................................................................28

��...........................................................................................................30

�� ...............32

!� �� ...........................................................................................34

CONTROL, INTERVENTION, AND PREVENTION ............................................................35

�� ......................................................................................................35

ii

�� ................................................................36

�� ...........................................................38

�� ..........................................................................................................38

FUTURE PREDICTIONS AND PERSPECTIVES..................................................................39

CONCLUSIONS AND RECOMMENDATIONS .....................................................................41

REFERENCES .............................................................................................................................42

ARTICLES ...................................................................................................................................59

iii

ACKNOWLEDGEMENTS

It feels as if I have travelled and spend more time with my laptop than with my wife and son;

Birgitte Plesning and Malte Hendriksen for the last two years why I sincerely want to thank them

for accepting my “absence”. I would never have managed to pull this off without their support.

I also want to thank Frank M. Aarestrup with whom I have worked for the last 16 years. It has

been a long and interesting journey and Frank has always given me opportunities to have an

impact on my daily work and duties. I am also honoured that he and Henrik C. Wegener had faith

in me and offered me the chance to initiate the Ph.D. study which was accepted by DTU despite

my lack of an academic degree.

I would like to thank Susanne Karlsmose for assisting / taking over many of my daily duties

leaving me with more time to study – it has been a great help. Talking about help – I would also

like to thank all the technicians in our group and especially Christina Aaby Svendsen and Berith

Kummerfeldt for outstanding technical assistance. Furthermore, I really appreciated the

assistance from Matthew Mikoleit from CDC, US, for reviewing the manuscripts / correcting the

English language style, and Frederic J. Angulo from CDC, US, for his thoroughness as co-author.

I would also thank Hanne-Dorthe Emborg, Antonio Vieira, and Sara M. Pires for tutoring me in

the SAS software and for lending me office space once in a while. Henrik Hasman also tutored

me and assisted in characterisation of resistance genes for which I am grateful.

I will also thank Aroon Bangtrakulnonth, Chaiwat Pulsrikarn, and Srirat Pornreongwong�from the

WHO National �� and �� Center, Thailand, for an excellent collaboration in

multiple studies and for their wonderful hospitality during my visits to Bangkok. In addition, I

want to thank all the co-authors for their valuable contributions to the manuscripts and members

of the Global Foodborne Infection Network for sharing data. Finally, I want to thank Patrick

McDermott from the US-FDA for reviewing this thesis and correcting the English language style.

iv

LIST OF ORIGINAL ARTICLES The thesis is structured as a review of the global epidemiology of non-typhoidal ��

(NTS) infections in humans and six articles that are published or submitted for publication in

peer reviewed international journals. Articles are referred in the text by roman letters and marked

in bold typeface.

I. Hendriksen RS, Mikoleit M, Carlson VP, Karlsmose S, Vieira AR, Jensen AB, Seyfarth

AM, Delong SM, Weill FX, Lo Fo Wong DM, Angulo FJ, Wegener HC, Aarestrup FM.

WHO Global Salm-Surv External Quality Assurance System (EQAS) for serotyping of

�� isolates, 2000 - 2007. J Clin Microbiol. 2009 Sep; 47 (9): 2729-36.

II. Hendriksen RS, Vieira AR, Karlsmose S, Mikoleit M, Lo Fo Wong DMA, Jensen AB,

Delong SM, Wegener HC, Angulo FJ, Aarestrup FM.

Global monitoring of �� serovar distribution based on quality assured data from

the WHO Global Salm-Surv Country Data Bank; 2001 – 2007. To be submitted to:

Foodborne Pathog Dis.

III. Hendriksen RS, Bangtrakulnonth A, Pulsrikarn C, Pornreongwong S, Hasman H, Song

SW, Aarestrup FM.

Antimicrobial resistance and molecular epidemiology of �� Rissen from animals,

food products, and patients in Thailand and Denmark. Foodborne Pathog Dis. 2008 Oct; 5

(5): 605-19.

IV. Hendriksen RS, Mikoleit M, Kornschober C, Rickert RL, Van Duyne S, Kjelsø C,

Hasman H, Cormican M, Mevius D, Threlfall EJ, Angulo FJ, Aarestrup FM.

Emergence of Multidrug-Resistant �� Concord Infections in Europe and the

United States in Children Adopted From Ethiopia, 2003–2007. Pediatr Infect Dis J. 2009

Sep; 28 (9): 814-818.

v

V. � Sirichote P, Hasman H, Pulsrikarn C, Schønheyder HC, Samulioniené J, Pornreongwong

S, Bangtrakulnonth A, Aarestrup FM, Hendriksen RS.

Molecular characterization of extended spectrum cephalosporinases (ESC) producing

�� Choleraesuis from patients in Thailand and Denmark. �� "�#�$� �

� %��bi��

VI. Hendriksen RS, Bangtrakulnonth A, Pulsrikarn C, Pornreongwong S, Noppornphan G,

Emborg HD, Aarestrup FM.

Risk Factors and Epidemiology of the Ten Most Common �� Serovars from

Patients in Thailand: 2002–2007. Foodborne Pathog Dis. 2009 Oct; 6 (8): 1009-19.

vi

RESUMÉGlobalisering, internationale rejser og handel øger hastigt den globale udbredelse og overførsel af

levnedsmiddelbårne patogener imellem lande. Allerede i dag er mere end halvdelen af alle

humane �� infektioner i Danmark forårsaget af internationale rejser og af importerede

fødevarer. I store dele af verden har �� serovar Enteritidis og �� Typhimurium

indtil nu tiltrukket sig mest opmærksomhed. Dog er andre �� serotyper ofte mere

udbredt i enkelte lande og resultere i flere alvorlige infektioner og udbrud. Det er således vigtigt

at undersøge epidemiologien af �� globalt.

Det er vigtigt, at data fra forskellige lande er sammenlignelige. Vi har vurderet kvaliteten af

��overvågningsdata fra laboratorier i hele verden samt deres evne til at serotype baseret

på deltagelse i WHO's Globale Foodborne Infections Network (GFN) External Quality Assurance

System (EQAS). Syv EQAS-runder blev gennemført mellem 2000 og 2007. Deltagende

laboratorier indsendte serotypningsresultater for otte �� isolater i hver runde. I alt deltog

249 laboratorier i 96 lande i mindst én EQAS runde. Totalt set indsendte 76% af de deltagende

laboratorier data for alle otte stammer og 82% af stammerne var korrekt serotypet.

Præstationsmæssigt blev der observeret regionale forskelle blandt laboratorier fra Centralasien og

Mellemøsten, som udførte testene mindre godt sammenlignet med de øvrige regioner. Fejl, som

resulterede i forkert identifikation af serotypen, var typisk forårsaget af vanskeligheder med at

detektere andenfasen af flagel antigenet eller differentiering indenfor antigen komplekser. Nogle

af disse fejl er sandsynligvis relateret til kvaliteten af den antisera, som har været til rådighed (I).

Baseret på data fra GFN Country Data Bank (CDB) i årene 2001 til 2007 sammenfattede vi den

globale fordeling af �� serotyper i udvalgte lande for at afdække de regionale og globale

tendenser og mønstre i forekomsten af �� serotyper. Sammendraget var baseret på

kvalitetssikrede data fra 37 lande, som alle har bestået kvalitetssikringskravet til GFN EQAS. Vi

har fundet betydelige forskelle imellem de mest almindeligt isolerede serotyper i forskellige

geografiske områder, hvorimod flere lignende serotyper blev rapporteret i lande fra det samme

område. Der blev også observeret en faldende tendens til at isolere og serotype i de lande som

indgår i denne undersøgelse. Et par serotyper dominerede i hele verden, men var til stede med

forskellig hyppighed i forskellige regioner. Vi bemærkede interessant nok, at globalt set er den

relative betydning af �. Enteritidis og �. Typhimurium faldende, mens andre serotyper såsom ��

Typhi, �� Infantis, �� Hadar, �� Newport, �� Virchow, �� Agona og andre serovars er stigende (II).

vii

En række ”case-studies” blev udført for at undersøge den globale spredning af ��. Den

genetiske diversitet og resistensprofilen blev undersøgt på 112 �� Rissen isolater fundet blandt

mennesker, fødevarer og dyr i Danmark og Thailand. Derudover blev risikofaktorer såsom ”at

rejse” og ”indtagelse af bestemte fødevarer” analyseret og evalueret. Der blev i alt observeret 63

unikke &��I pulsed field gel elektroforese (PFGE) mønstre, hvoraf det dominerende mønster blev

delt af 22 stammer. Der blev observeret et begrænset niveau af antibiotikaresistens i de danske

stammer, hvorimod der blev observeret en højere grad af resistens i stammer fra Thailand.

Statistiske analyser og molekylær subtypning identificerede kombinationen af ”rejse til Thailand”

og ”konsumering af importerede svin / svinekødsprodukter” samt ”konsumering af svin /

svinekød produceret i Danmark”, som risikofaktorer for �� Rissen-infektioner blandt danske

patienter (III).

Der er blevet rapporteret om multiresistente �� Concord infektioner blandt børn adopteret fra

Etiopien til Østrig, Danmark, England (og Wales), Irland, Holland og USA. Vi interviewede

patienter, karakteriserede isolater og indsamlede oplysninger om adoptioner fra Etiopien for at

vurdere konsekvenserne for folkesundheden. Isolaterne er blevet subtypet ved brug af PFGE og

resistensprofiler; specifikke resistens-gener er blevet karakteriseret. Adoptionsstatus var

tilgængelig for 44 patienter <3 år, hvoraf 98% var blevet adopteret fra Etiopien. De adopterede

børn kom fra forskellige børnehjem i Etiopien. På de besøgte børnehjem var der dårlig hygiejne

og sanitære forhold samt hyppig brug af antibiotika. Der var 53 PFGE mønstre blandt 64 ��

Concord isolater. Der blev udført resistensbestemmelser på 43 isolater, hvoraf 81% var

multiresistente (� 3 stoffer). De multi-resistente isolater var fra etiopiske adoptivbørn og var

resistente over for tredje og fjerde generations cephalosporiner. Herudover havde 14% nedsat

følsomhed over for ciprofloxacin (IV).

Vi har også karakteriseret 24 udvidet spektrum cefalosporinase-producerende isolater af ��

Choleraesuis fra thailandske og danske patienter. Treogtyve af isolaterne var fra thailandske

patienter fra år 2003, 2007 eller 2008. Yderligere var et af isolaterne fra en dansker, som havde

været rejsende i Thailand. De 13 af isolaterne var fra blodprøver. MIC-bestemmelse, micro-array,

PCR, plasmid-profilering og replikon-typning har afsløret forekomst af multiresistente isolater

med plasmider der varierer i størrelse fra 75 -200 kb indeholdende enten ��CMY-2 inklusiv inc

A/C eller ��CTX-M-14 inklusiv incFIIA / incFrepB. RFLP og replikon-typning fordelte isolaterne i

fire adskilte grupper. PFGE afslørede 16 unikke mønstre og fem grupper. Isolatet fra den danske

viii

patient var identisk med to kliniske isolater fra Thailand. Undersøgelsen viste fremkomsten af

��CTX-M-14 genet blandt adskillige kloner af ��Choleraesuis. Adskillige plasmider blev

identificeret indeholdende op til to forskellige udvidet spektrum cefalosporinase gener og fire

forskellige replikonner. En rejse-associeret spredning blev bekræftet (V).

De fleste undersøgelser af epidemiologien af �� er fra lande, hvor �� Enteritidis og ��

Typhimurium var dominerende. Der ses dog et andet mønster i Thailand, hvor vi har foretaget et

retrospektivt observationsstudie fra 2002 til og med 2007 for at vurdere epidemiologiske

tendenser og risikofaktorer forbundet med de ti mest almindelige �� serotyper isoleret

fra mennesker. Der blev inkluderet i alt 11.656 �� isolater i undersøgelsen dækkende alle

seks år. De fleste af isolater var fra patienter <5 år (33%), isoleret i juni (13%), fra fæces (82%)

og fra Bangkok (27%). Statistiske analyser viste, at �. Enteritidis og �. Choleraesuis blev isoleret

fra blod med en højere frekvens end andre ikke-typhoide serotyper. Der var en tendens til at

begge serotyper blev isoleret fra patienter ældre end 5 år. �� Choleraesuis blev fundet med en

højere frekvens i patienter fra Bangkok og den centrale region, mens�� Enteritidis overvejende

blev fundet i patienter fra den sydlige region. Undersøgelsen viser også i forhold til tidligere

undersøgelser et skift i forekomsten af de mest almindelige �� serotyper forbundet med

humane infektioner i Thailand. Der var blandt andet en stigning i humane infektioner med ��

Stanley, �� Corvallis, og �. Choleraesuis, som tidligere har været forbundet med svin. Yderligere

var der et fald i infektioner forårsaget af �� Weltevreden og �� Anatum (VI).

Samlet set har denne Ph.D. afhandling vurderet kvaliteten af �� serotypning foretaget på

de nationale referencelaboratorier samt brugt disse data til at beskrive udviklingen i den globale

distribution af ��. Desuden har den vist forbindelser imellem forskellige reservoirer og

kilder til salmonellosis hos mennesker i forskellige områder af verden og anvendt thailandske

overvågningsdata til at opstille risikofaktorer for salmonellose hos mennesker i Thailand. Den er

kommet med flere anbefalinger til aktioner, hvad angår kontrol samt forebyggelse af infektioner i

mennesker.

ix

SUMMARYGlobalization, international travel, and trade among countries facilitate the rapid global spread

and transmission of food borne pathogens. Currently, more than half of all human ��

infections in Denmark result from international travel and consumption of imported food.

Worldwide,�� serovar Enteritidis and �� Typhimurium cause the majority of

human clinical cases. However, other �� serovars are often more prevalent in specific

countries, and result in more sever infections and outcome. It is, thus, important to study

�� epidemiology globally.

It is essential that data from different countries are comparable. We assessed the quality of the

�� surveillance data worldwide, and the laboratories ability to accurately determine

serotype, based on participation in the WHO Global Foodborne Infections Network (GFN)

External Quality Assurance System (EQAS) for serotyping of �� Seven EQAS

iterations were conducted between 2000 and 2007. In each iteration, participating laboratories

submitted serotyping results for eight ��isolates. A total of 249 laboratories in 96

countries participated in at least one EQAS iteration. Cumulatively, 76% of participating

laboratories submitted data for all eight strains and 82% of strains were correctly serotyped.

Regional variations in performance were observed, with higher error rates in laboratories in

Central Asia and the Middle East compared with other regions. Errors that resulted in incorrect

serovar determinations were usually caused by difficulties either in the detection of the phase II

flagellar antigen or differentiation within antigen complexes. Some of these errors likely were

related to the quality of the antisera available (I).

We summarised the global distribution of �� serovars of selected countries, based on

2001-2007 data from GFN Country Data Bank (CDB) to uncover regional and global trends in

the occurrence of �� serovars. The summary was based on quality-assured data from 37

countries that passed the quality assurance threshold of the GFN EQAS. We found considerable

differences in the most commonly isolated serovars in various geographical regions, and more

similar serovars prevalences in countries from the same region. We observed a tendency among

countries included in this study to isolate and serotype less compared to previous years. A few

serovars predominated worldwide, but were present with different frequencies in different

regions. Interestingly, we observed that the relative importance of �� Enteritidis and ��

x

Typhimurium is decreasing globally, while other serovars such as �� Typhi, �� Infantis, �� Hadar,

�� Newport, �� Virchow, �� Agona and other serovars are increasing (II).

A number of case studies were conducted to investigate the global spread of ��. The

genetic diversity and antimicrobial resistance of 112 �� Rissen isolates recovered from humans,

food products and animals in Denmark and Thailand were examined. Additionally, risk factors

due to travel and consumption of specific food products were analyzed and evaluated. A total of

63 unique &��I pulsed field gel electrophoresis (PFGE) patterns were observed. The predominant

pattern was shared by 22 strains. Limited antimicrobial resistance was observed in the Danish

strains, whereas a higher degree of resistance was observed in strains originating from Thailand.

Statistical analysis and molecular subtyping identified the combination of “travel to Thailand”

and “consumption of imported pig / pork products” as well “consumption of as pig / pork

products produced in Denmark” as risk factors for ��Rissen infection among the Danish patients

(III).

Multidrug-resistant �� Concord infections have been reported from children adopted from

Ethiopia to Austria, Denmark, England (and Wales), Ireland, the Netherlands and the United

States. We interviewed patients, characterized the isolates, and gathered information about

adoptions from Ethiopia to assess public health implications. Isolates were subtyped by PFGE

and antimicrobial susceptibility; specific antimicrobial resistance genes were characterized.

Adoption status was known for 44 patients <3 years of age; 98% were adopted from Ethiopia.

The children adopted from Ethiopia were from several orphanages; visited orphanages had poor

hygiene and sanitation and frequent use of antimicrobial agents. Sixty-four ��Concord isolates

yielded 53 PFGE patterns. Antimicrobial susceptibility was performed on 43 isolates; 81% were

multidrug-resistant (�3 agents). Multidrug-resistant isolates were from Ethiopian adoptees and

were resistant to third and fourth generation cephalosporins, with 14% showing decreased

susceptibility to ciprofloxacin (IV).

We also characterized 24 extended spectrum cephalosporinases (ESC) producing isolates of ��

Choleraesuis recovered from patients in Thailand and Denmark. Twenty-three isolates were

recovered from Thai patients in 2003, 2007, or 2008 and one isolate was recovered from a Danish

traveler to Thailand, 13 of which were blood culture isolates. MIC determination, micro-array,

PCR, plasmid profiling and replicon typing revealed the presence of multi-drug resistant isolates

harboring either ��CMY-2 containing incA/C or ��CTX-M-14 containing incFIIA / incFrepB

xi

plasmids ranging in size from 75–200 kb. The RFLP and replicon typing clustered the isolates

into four distinct groups. PFGE revealed 16 unique patterns and five clusters. The isolate from

the Danish patient was indistinguishable from two Thai clinical isolates. This study revealed the

emergence of the ��CTX-M-14 gene among several clones of �� Choleraesuis. Numerous plasmids

were identified containing up to two different ESC genes and four distinct replicons. A “travel

associated” spread was confirmed (V).

Most studies of �� epidemiology have been in countries were��Enteritidis and ��

Typhimurium predominated. In Thailand, a different pattern is observed. We conducted a

retrospective observational study to assess epidemiological trends and risk factors associated with

the ten most common �� serovars isolated from humans in Thailand between 2002 and

2007. A total of 11,656 �� isolates covering all six years were included in the study.

Most isolates were from patients <5 years (33%), isolated during June (13%), recovered from

stool (82%) and from Bangkok (27%). Statistical analysis revealed that ��Enteritidis and ��

Choleraesuis were recovered from blood with a higher frequency than other non-typhoidal

serovars. While both serovars tended to be isolated from patients older than 5 years; ��

Choleraesuis was recovered with a higher frequency from patients in Bangkok and the Central

Region, whereas ��Enteritidis was recovered predominantly from patients in the Southern

Region.�This study also indicates a shift in prevalence of the most common �� serovars

responsible for human infections in Thailand compared to previous studies. Notably, there was an

increase in human infections with �� Stanley, �� Corvallis, and �� Choleraesuis - three serovars

which previously have been associated with swine - and a decrease in infections due to ��

Weltevreden and �� Anatum (VI).

Overall, this Ph.D. thesis has assessed the quality of �� serotyping conducted in national

reference laboratories and used these data to describe trends in the global distribution of

��. In addition, it has revealed links between different reservoirs and sources to human

salmonellosis in different areas of the world and used Thai surveillance data to set up risk factors

for human salmonellosis in Thailand. In several cases, this work has resulted in recommendations

to help control and prevent infections in humans.

xii

BACKGROUNDToday, we are all residents of a global village. The expanding trade of food and livestock, and

increased human travel and migration are means of spreading infectious disease irrespective of

national borders. This makes infectious disease control and food safety important for all

countries. In Denmark, it is expected that in a few years, around 2/3 of all food products will

originate from other countries. Already today, more than half of all human �� infections

in Denmark are caused by international travel and consumption of imported food.

In addition, the majority of the �� isolates causing human infections in Denmark by

consumption of imported food products are resistant to multiple antimicrobials, which has

increased in many countries that export foods to Denmark.

In Europe and North America,�� Enteritidis and �� Typhimurium have, up until now, drawn most

attention. However, other �� serovars are often more prevalent in other parts of the

world and result in more sever infections with higher morbidity. Thus, there is an urgent need to

further investigate and elucidate the occurrence, international spread, and global epidemiology of

�� serovars and specific clones so that evidence-based interventions can be taken

worldwide.

PURPOSE The purpose of the PhD project was to study the global epidemiology of NTS infections in

humans. The term “epidemiology” is defined in the traditional way as the study of the occurrence

and distribution of a disease in a population and the factors which influence disease occurrence.

The PhD project integrated conventional and molecular microbiology used to characterise

isolates with epidemiological and statistical tools needed to estimate trends and risk factors.

RESEARCH APPROACH The projects were derived from the activities of the WHO Global Foodborne Infections Network

(GFN), a network of institutions building capacity for laboratory-based surveillance of foodborne

pathogens and disease (http://www.who.int/salmsurv/en/), to assess the global distribution of

xiii

xiv

�� serovars, investigate examples of international spread and identify regional and local

risk factors for infection.

The specific studies conducted during this PhD project focused on the following objectives:

1. To assess the quality of the �� surveillance data worldwide and the laboratories

ability to serotype based on participation in the GFN EQAS.

2. To estimate the global distribution and trends of �� serovars from the GFN

Country Data Bank (CDB). CDB data reliability was based on results from the GFN

EQAS.

3. To investigate the spread of �� Rissen caused by international travel to Thailand and

imported food from Spain and Germany.

4. To investigate the spread of �� Concord to Europe and United States through adopted

children from Ethiopia.

5. To characterise the extended spectrum cephalosporinases genes of the invasive serovar ��

Choleraesuis.

6. To identify risk factors in the epidemiology of �� serovars in Thai patients and

to use these findings to recommend strategies for control and prevention.

INTRODUCTION�� is a genus of rod-shaped, Gram-negative, oxidase negative, non-spore forming,

predominantly motile (peritrichous) bacteria belonging to the family '� �� .

�� are approximately 0.7 to 1.5 �m wide and 2.0 to 5.0 �m in length (Giannella � ��.,

1996). The bacterium ferments glucose and usually with production of gas. In addition, they are

able to grow in a minimal media containing glucose as the sole carbon energy source and

ammonium ion as a nitrogen source (prototrophic). Most serovars are phenotypically identified

by urea hydrolysis, the absence of tryptophan deaminase, non-lactose fermentation, the

production of hydrogen sulphide (H2S), decarboxylate lysine and ornithine and growth on

Simmons citrate agar (Grimont � ��., 2000).

The genus ��, first known as ��, was initially discovered in 1886

by Theobald Smith and Daniel Elmer Salmon. The discovery of the genus originated from the

work on swine fever (hog cholera) by Theobald Smith and he named the genus after his

supervisor at the U.S. Department of Agriculture (USDA), Daniel E. Salmon (Grimont � ��.,

2000).

In the late 19th century, serological tests utilizing agglutination with antiserum were developed,

and new serovars were discovered and named after either clinical conditions or hosts, e.g.

�� ,�� ,��,��

��,�and�� (Grimont � ��., 2000).

In 1926, Bruce White developed the analysis of somatic and flagella antigens, which in 1961 was

expanded by Fritz Kauffman to distinguish more than 2000 serovars. In 1980, the ��

nomenclature of today (The Kauffman-White Scheme) was proposed, and is currently maintained

by the World Health Organization (WHO) Collaborating Centre for Reference and Research on

�� at the Pasteur Institute, Paris, France (Grimont � ��., 2000; Grimont � ��., 2007).

Currently, �� consists of 2.579 different serovars divided into two species – ��

�� (n=2.557) replacing the old name �� (Hohmann � ��., 2001) and

��(n=22) (Grimont � ��., 2007). The species, �� is further

divided into six subspecies -�� subsp�� (I), �� subsp.

�� (II), �� subsp. ��(�� (IIIa), �� subsp. ��(��

(IIIb), �� subsp. �� (IV), and �� subsp. �� (VI).

Serovars of �� subsp�� (I), are primarily named by the geographical

1

origin such as �� Amsterdam, �� Panama, and �� Derby whereas the serovars of the remaining five

subspecies all are named by antigenic formular (Grimont � ��., 2000; Grimont � ��., 2007).

GLOBAL DISTRIBUTION OF SEROVARS AND TRENDS IN

HUMANS�� serotyping still serves as the predominately used surveillance tool for detection of

outbreaks and corresponding sources, to monitor trends over time, and attribute different food

and animal reservoirs to human infections. Despite this, there is today only limited knowledge of

the global distribution of �� serovars in humans. In the last decade, some countries have

collected annual prevalence data on serovar distribution among humans, but very few

publications have summarised the global distribution of the serovars responsible for human

infections and further analysed the data (Herikstad � ��., 2002; Galanis � ��., 2006; II). An

equally important feature for surveillance is quality assurance and quality control, which is

necessary to ensure reliable data. Only a small number of international quality assurance systems

exist to evaluate the quality of the serotyping conducted worldwide by national reference

laboratories (Petersen � ��., 2002; Anonymous, 2007b; I).

In January 2000, the WHO launched WHO Global Foodborne Infections Network (GFN)

(formerly known as Global Salm Surv (GSS)), a global effort to enhance laboratory-based

surveillance of ��infections and other foodborne diseases, and to promote prevention

and control activities. Enhancing worldwide serotyping of ��is a key objective of WHO

GFN and is facilitated by bench training at international capacity building courses.

To ascertain the performance of participating laboratories, and thereby promote enhanced

laboratory-based surveillance, an External Quality Assurance System (EQAS) was established as

a part of WHO GFN in 2000 (Petersen�� ., 2002; I). Each year, EQAS distributes a set of

blinded bacterial cultures for identification, serotyping and antimicrobial susceptibility testing. A

key component of this program is the Internet based Country Data Bank (CDB), to which

member countries are encouraged to annually upload data on the 15 most common ��

serovars (http://www.antimicrobialresistance.dk).

The results of the WHO GFN EQAS data from 2000 to 2007 revealed that a total of

2

249 laboratories in 96 countries participated in annual EQAS testing at least once (Figure 1) (I).

)��*��$�� +��,��-�+�� ,�� '.�� $�� .�� '.�� $/0�� -�� -�� $/0�� $�� +��,�� +I; II,��

During the seven EQAS iterations, a total of 756 reports were received from the participating

laboratories. Cumulatively, 76% of participating laboratories submitted data for all eight strains

and 82% of the strains were correctly serotyped. The goal of the EQAS program is for all

participating laboratories to perform ��serotyping with a maximum of one error. The

percentage of laboratories reaching the threshold reporting one or zero errors increased

significantly (�=0.04), from 48% in 2000 to 68% in 2007. In each EQAS iteration, 84% to 96%

of the laboratories correctly serotyped the ��Enteritidis isolate that was included in the panel of

test strains as an internal quality control strain. Regional variations in performance were

observed, with laboratories in Central Asia and the Middle East performing less well overall than

other regions. Errors that resulted in incorrect serovar identification were usually caused by

difficulties in the detection of the phase II flagellar antigen, or differentiation within antigen

complexes. Some of these errors likely are related to the quality of the antisera available (I). The

same conclusion, that the main problem existed in detecting the H antigens, was reached by the

National Institute for Public Health and the Environment (RIVM) which served as the

3

4

community reference laboratory for �� as designated by the European Commission.

They evaluated 26 European national reference laboratories in 2007 and found that 98% and 96%

of the laboratories correctly serotyped the isolates using O and H antigen, respectively

(Anonymous, 2007b).

In 2008, the global distribution of �� serovars per country, based on data from the WHO

GFN CDB, were summarised and analysed in search for trends from 2001 to 2007. All data

included were based on reliable data from countries which managed the quality assurance

threshold of the WHO GFN EQAS (Figure 1) (V).

The data showed that, in all regions with exception of the Oceania and North American,��

Enteritidis and ��Typhimurium ranked as the first and second most common serovars,

respectively. In the North American and the Oceania regions these two serovars ranked in the

opposite order. Globally the

overall proportion for both

serovars decreased over time

with �� Enteritidis decreasing

from 44.2% to 41.5% and ��

Typhimurium decreasing from

18.9% to 15.0% (Figure 2) (V).

This was mainly due to a

significant decreasing trend )��1��!�� 23�� +V,

(p<0.01) in the proportion of ��

Enteritidis in developing

countries and a non-significant

decreasing trend (p=0.16) in

the proportion of ��

Typhimurium in developed

countries.

In addition to ��Enteritidis and

��Typhimurium, �� Infantis

was among the serovars )��2��!�� 23�� +V,

observed in all regions. Globally, the overall proportion of �. Infantis increased over the years,

from 1.5% to 2.2%. However, no statistically significant increasing trend was detected (p=0.76)

(Figure 3). �. Infantis ranked as the fifth most common serovar in the European region. �� Agona

was frequently observed in Asia and Latin America, ranking as the third most common serovar.

�� Agona also ranked as the top seven serovar in Europe and the top 13 in North America.

Overall, the proportion of this serovar increased from 0.8% to 1.5% between 2001 and 2007.

A slight decrease in the overall proportion over time was seen for �� Heidelberg, from 2.5% to

2.3% (Figure 3). This serovar was more common among developed countries. ��Heidelberg

ranked in top four in North America. However, lower frequencies were seen in Europe (top 9)

and Latin America (top 19).

�� Virchow was common only in Asia, Europe and the Oceania regions, but with a high

proportion. The overall proportion oscillated over the years (Figure 3) and, since 2005, an

increase was seen among developed countries while a similar proportionate decrease was

reported by developing countries.

High frequencies of �� Thompson were seen in Europe and North America. ��Newport also was

reported as a top serovar by these two regions, in addition to Latin America. Nevertheless, the

overall proportion over time of �� Newport, which was increasing in the initial years, decreased

from 5.0% in 2005 to only 1.2% in 2007 (Figure 3).

�� Oranienburg was observed only in North and Latin America, ranked 10th and 15th, respectively.

�� Hadar and �� Montevideo were reported by almost all regions, however, the frequencies varied

considerably. �� Hadar ranked 3rd in Europe, but lower in the other regions. In general, the overall

proportion remained at similar levels over the years, with the exception of a slight decrease in

2005 (Figure 3). Finally, �� Montevideo was more common in North and Latin America while ��

Saintpaul was more predominant in Oceania and North America. These two serovars exhibited

similar trends over time, increasing from 2003 to 2005, followed by a decline in 2007 (Figure 3).

The survey concluded large differences among the top 20 most commonly isolated serovars

between regions but lesser differences between the top 15 most commonly isolated serovars

between countries within the same region. Nevertheless, a few serovars are more frequent than

others in many of the regions and countries.

Several national surveillance reports and scientific articles support the observations described by

Hendriksen � ��. (II). In Europe, surveillance data from 23 countries between 2006 and 2007

5

among humans showed that �� Enteritidis was ranked first, but decreasing, and that ��

Typhimurium was fairly consistent over time and ranked second (Anonymous, 2009b). In

addition, �� Infantis was ranked third followed by �� Virchow (top 4), �� Newport (top5), and ��

Hadar (top 7). However, both �� Thompson and �� Heidelberg were not listed among top 10

among the 23 countries in Europe (Anonymous, 2009b). In the United Kingdom, data from 1983

to 2007 revealed the same ranking of �� Enteritidis and �� Typhimurium as for all Europe but

with a decreasing tendency for both serovars (Anonymous, 2007f). In contrast, the Danish data

from 2007 showed an opposite ranking of �� Enteritidis and �� Typhimurium (Anonymous,

2009a). In South America, �� Typhimurium�was ranked first and �� Enteritidis second in 2008

(Anonymous, 2008c). In addition, the data also showed that �� Isangi was highly frequent and

ranked third followed by ��Dublin and �� Virchow (Anonymous, 2008c).The same tendency of

ranking �� Enteritidis and �� Typhimurium was observed since 1997 in the United States (Olsen

� ��., 2001; Anonymous, 2008e), in China (Henan province) between 2006 and 2007 (Xia � ��.,

2009), and Taiwan between 1998 to 2002 (Lauderdale � ��., 2006). Also in India, ��

Typhimurium was ranked before�� Enteritidis between 2001 to 2005 (Kumar � ��., 2009) and in

New Zealand in 2005 to 2008 (Anonymous, 2008a).

In the United States, ��Newport was ranked third followed by ��Heidelberg (Anonymous,

2008e). The distribution of serovars in Southeast Asia is slightly different from the global trend

in general. In the Philippines, Hong Kong, and Sri Lanca, �� Typhimurium was ranked before��

Enteritidis whereas it was the opposite in Singapore, South Korea, and Thailand (Lee � ��., 2009;

VI). However, in most of these countries another non-typhoidal�� (NTS) ranked either

as the top serovar or in between �� Enteritidis and �� Typhimurium in prevalence. In general, the

serovars following �� Typhimurium and�� Enteritidis were �� Weltevreden, ��Stanley, ��

Choleraesuis, �� London, �� Agona, �� Rissen, �� Anatum, �� Panama, and �� Virchow (Lee � ��.,

2009, VI). In Taiwan, the distribution of serovars revealed large similarities with Southeast Asia.

Here, ��Stanley was listed as the third most common serovar followed by �� Schwarzengrund, ��

Newport, ��Albany, ��Virchow, �� Weltevreden, and �� Agona (Lauderdale � ��., 2006). China

(Henan province) did not share the same serovars as Taiwan. In Henan province, ��Derby ranked

third followed by �� Indiana, �� Litchfield, �� Thompson, and �� Agona (Xia � ��., 2009).

The complexity of the global distribution of �� serovars in humans is enormous as it is

influenced by multiple factors such as animal and environmental reservoirs and complex route of

6

transmission. It will be important for the future to extend the global understanding of the

epidemiology of �� in not only humans but also in all animal reservoirs.

HUMAN EPIDEMIOLOGY ��

Food-borne diseases have been estimated to infect up to 76 million people in the United States

annually. This would equal one fourth of the people infected in the developed world per year if

these data were extrapolated. The burden of salmonellosis is expected to be much greater in the

developing parts of the world (Schlundt � ��., 2004). �� is overall the most common

food-borne pathogen in the United States, however, in some states $�� is more

prevalent than �� (Anonymous, 2009c). In Europe, $�� are more frequent

than �� (Anonymous, 2008d)��According to the WHO, humans NTS infections

constitute a major public health burden on society and represent a huge cost for many countries

(www.who.int). In 2000, it was estimated that in the United States, NTS resulted in 1.4 million

infections annually in a population of about 293 million inhabitants with approximately 168.000

visits to the general practitioner (GP). A total of 16.430 people were hospitalized resulting in 582

deaths (Mead � ��., 1999; McDermott � ��., 2006). A similar study was conducted the same year

in the United Kingdom. This revealed that 41.616 NTS cases occurred each year with 15.036

laboratory confirmations among a population of 60 million people, resulting in 1.516

hospitalization and 119 deaths (Adak � ��., 2002; McDermott � ��.,2006). This was

approximately twice as many hospitalizations and deaths in the United States compared to the

United Kingdom.

Recently, the financial burden of NTS was estimated in the United States based on FoodNet data.

The data revealed that costs of medical care, lost productivity, and mortality exceeded more that

$ 3.6 billion annually (Voetsch � ��., 2004; McDermott � ��., 2006). In comparison, the annually

costs of NTS in Denmark are estimated to be $ 15.5 million which was approximately four time

less that in the United States (www.who.int).

A few countries around the world have an established laboratory-based surveillance of NTS, or

have recently improved the data quality and reporting to implement programmes measuring the

burden of salmonellosis. One of the measurements in the surveillance reports are the notification,

incidence, or isolation rate per 100.000 inhabitants all estimating the burden on the society

7

caused by salmonellosis (Figure 4) (Bangtrakulnonth and Tishyadhigame; 2006; Aissa � ��.,

2007; Anonymous, 2008c; Anonymous, 2008d; Anonymous, 2008e).

In the United States, the National �� Surveillance System reported in 2006 an increase

of 12.3% of NTS compared with 2005 due to increased reporting. In general, the level decreased

compared with data from 1996 (Anonymous, 2008e). The number of human �� cases

also seems to have declined in Tunisia based on data collected from 1994 to 2004 with the lowest

isolation rate monitored in 2004 for the entire surveillance period (Aissa � ��., 2007). The 2008

Annual Surveillance Report from New Zealand showed, as many other country reports, a

decreasing notification rate of NTS (Anonymous, 2008a). Based on data from 29 countries, the

number of salmonellosis cases in Europe decreased by 8% between 2005 and 2006 (Anonymous,

2008d). In 2006, the National �� and �� Center in Thailand found 3.758 NTS

cases, representing a decrease compared with previously published data showing the number of

human cases from 1993 to 2002 (Bangtrakulnonth � ��., 2004).

The worldwide reported trend of decreasing human cases caused by NTS seems to be in

agreement with what have been observed elsewhere. A decreasing number of �� isolates

were serotyped from 2001 to 2007 when assessing the global distribution of �� serovars

in 37 countries worldwide. The data were based on quality data submitted to CDB of the WHO

Notification rate in the US, 2006: 13.6 / 100.000 inhabitants Notification rate in the EU, 2006: 34

/ 100.000 inhabitants

Isolation rate in Tunisia, 2004 : 1.9 / 100.000 inhabitants

Incident rate in South Africa 2008: 1.9 / 100.000 inhabitants

Isolation rate in Thailand 006: 25.7 / 100.000 inhabitants

Notification rate in New Zealand 2008: 31.5 / 100.000 inhabitants

)��4��'5�� -��+0�� 6�17786�� 17736��1779�6��1779�6��1779�,��

8

GFN (II). Despite the decreasing occurrence of NTS infections in human, the problem is still

large and is largely preventable and therefore an unnecessary burden on public health.

�

��

The symptoms of �� infections usually appear 12 to 72 hours after ingestions of the

organism, and include diarrhea, fever, abdominal cramps, nausea, and sometimes vomiting but

asymptomatic infections may also occur. The illness usually lasts from 4 to 7 days but are in most

cases self limiting (www.cdc.gov; www.who.int; McDermott � ��., 2006; Anonymous, 2007f).

NTS gastroenteritis will develop into bacteremia in about 5% of cases. Bacteremia often requires

hospitalization with a prolonged course of illness and could potentially result in a fatal outcome

(Hohmann � ��., 2001; Jones � ��., 2008). A cohort study with almost 49.000 participants

showed that people with gastrointestinal infections caused by NTS have an excess mortality with

a relative risk of 13.31 up to a month after being infected (Helms � ��., 2003). Several studies

have described certain serovars such as �� Dublin and ��Choleraesuis often being associated with

invasiveness (Hohmann � ��., 2001; Helms � ��., 2002; Chiu � ��., 2004; Jones � ��., 2008; V;

VI).

An observational study based on patient data from 11.656 isolates (2002 – 2007) estimated the

risk factors of the ten most common �� serovars from Thai patients. The data showed

that 87.4% of 681 �� Cholereasuis isolates originated from blood samples with a significant

increased odds ratio of 44.00 (95% CI 34.3 – 56.5) when compared to other NTS serovars. ��

Enteritidis, �� I [1],4,[5],12:i:-, ��Typhimurium, and �� Panama did also seem to be highly

invasive when compared to other NTS serovars (VI). These data correspond well with an

investigation describing the differences in the outcome of salmonellosis based on the various

serovars (Jones � ��., 2008). Sixty percent and 67% of all �� Choleraesuis and �� Dublin

infections, respectively, require hospitalization compared with other serovars. However, ��

Heidelberg, �� Poona, �� Panama, ��Virchow, �� Paratyphi B var. Java and �� Sandiago also

seemed to more frequently cause invasive diseases (Jones � ��., 2008).

Several studies have shown that invasive NST is endemic in sub-Saharan Africa (Morpeth � ��.,

2009; Vandenberg � ��., 2009). In some of those countries the mortality in children caused by

NST bacteremia exceeds the burden of childhood malaria (Morpeth � ��., 2009). In the

Democratic Republic of Congo, a retrospective study from 2002 to 2006 in one hospital showed

9

that 59% of all bloodstream infections in children were caused by NTS. The data revealed that ��

Enteritidis and �� Typhimurium were responsible for up to 82.8% of the cases (Vandenberg � ��.,

2009). The study highlighted that many NTS invasive infections were nosocomial and resulted in

prolonged hospitalization, posing a significant problem in developing countries. Little is known

about human NTS infections in Africa and many other developing countries, but the limited data

have shown that NTS infection often are associated with invasiveness and severe outcome. There

is an urgent need to address this problem in order to elucidate the mechanisms responsible for the

severe outcomes.

��

Human�� infections are age specific and affect mostly children, elderly people and

immunological compromised patients (Hohmann et al., 2001; Anonymous, 2008c; Anonymous,

2008d; Anonymous, 2008e; Jafari et al, 2009; VI).

Average

0,05,0

10,015,020,025,030,035,0

0-5

6-10

11-1

5

16-2

0

21-2

5

26-3

0

31-3

5

36-4

0

41-4

5

46-5

0

51-5

5

56-6

0

>60

Age groups

Cas

es in

per

cent

ages

The reason for the typical age pattern is believed to be a result of children acquiring immunity to

��, and deteriorating

immune status in the elderly. This

observation was supported by

Hendriksen � �� who showed that

from 2002 to 2007 in Thailand,

32.6% of all �� cases were

observed among children from 0 to 5

years of age and peaked again with

14.0% of all cases in people older

than 60 years in Thailand (Figure 5) (VI). The previously mentioned risk factor analysis from

Thailand showing an odds ratio between 1.63 (95% CI 1.1-2.5) and 1.51 (95% CI 1.1-2.0) in the

age group of 6-20 and 21-40 years for being infected with��Choleraesuis compared to other

NTS infections (VI). In the risk factor analysis, additional serovars seemed to be age specific

such as ��Anatum, �� Enteritidis, and ��Weltevreden, which mainly affected people older than 6

years. In contrast, ��Stanley, �� Panama, and �� I [1],4,[5],12:i:- predominately infected children

less than 6 years of age (VI).

)��:��/� �� - ��1771��1773�+VI,

10

0

200

400

600

800

1000

1200

1400

1600

Janu

ary

Februa

ryMarc

hApri

lMay

June Ju

ly

Augus

t

Septem

ber

Octobe

r

Novem

ber

Decem

ber

Months

no. o

f cas

es

S.Enteritidis

S.Stanley

S.Weltevreden

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S.Corvallis

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Others

)��8�� -��1771��1773�+VI,�

Several surveillance reports have illustrated the general infection pattern of human salmonellosis

associated with yearly seasonality, with the summer months being the season having the highest

incidence of infections (Anonymous, 2008a; Anonymous, 2008c; Anonymous, 2008d; Cho � ��.,

2008; VI). In Tunisia, however, this general pattern of infection seemed not to be consistent with

the hypothesis that most infections occur in the summer months. �� Enteritidis infections peaked

in January followed by�� Livingstone peaking in April, whereas �� Corvallis peaked in October

(Ben-Aissa � ��., 2007). Ben-Aissa � ��. did not indicate a reason for the skewed seasonal

pattern but one possibility could

be that this was the same time of

the year when the serovar peaked

in the animal reservoir. In

Thailand, the seasonality of

�� infections were in

general in agreement with other

studies having most infections in

the summer period (Figure 6) (VI).

Nevertheless, Hendriksen � ��.

describe that infections caused by

��Enteritidis had the highest

odds ratio of 1.2 (95% CI 1.0-

1.5) during the winter time. For infections caused by �� I [1],4,[5],12:i:- and�� Panama, however,

spring time seemed to constitute the highest risk with an odds ratio of 1.8 (95% CI 1.5-2.3) and

1.5 (95% CI 1.2-2.0). ��Choleraesuis was observed to pose the highest risk with an odd ration of

1.4 (95% CI 1.1-1.9) during autumn (VI) which was supported by another study (V).

The use of available surveillance data for descriptive analysis and source attribution, or even

more advanced analysis, should be of a high priority of all countries in order to facilitate a more

direct and targeted effort to minimize the burden of salmonellosis in high risk populations.

��

Antimicrobial treatment is not routinely recommended for empiric treatment of gastrointestinal

infections caused by NTS in healthy people as the infection often is self limiting. Antimicrobial

11

treatment should be given to patients with severe illness, immunosuppression or patients

suffering from bacteraemia (Hohmann � ��., 2001). Treatment with first line antimicrobials

should include ampicillin, chloramphenicol or trimethoprim + sulfamethoxazole (Hohmann � ��.,

2001; McDermott � ��., 2006). The choice differs by region and chloramphenicol is not used in

most developed countries, but is common in developing countries. Ampicillin and trimethoprim +

sulfamethoxazole are good choices, but many do not even considering them and choose in stead

fluoroquinolone or 3rd generation cephalosporins.

Unfortunately, the recent increased development of resistance to many antimicrobials often

leaves the GP with no alternative than to treat the infection with either a fluoroquinolone or 3rd

generation cephalosporins. These antimicrobials are routinely used for empiric treatment if the

susceptibility of the isolates is unknown or if the patient suffers from bacteremia (Hohmann � �

�., 2001). For paediatric patients, treatment with a fluoroquinolone is contraindicated, and

practitioners will rely on ceftriaxone or another 3rd generation cephalosporin (Hohmann � ��.,

2001).

Several studies from the United States, Canada and Denmark have shown an increased risk of

hospitalization or even death associated with multi-drug resistant NTS compared with

pansusceptible NTS. (Holmberg � ��., 1987; Lee � ��., 1994; Mølbak � ��., 1999; Helms � ��.,

2002; Martin � ��., 2004; Helms � ��., 2004; Varma � ��., 2005a; Varma � ��., 2005b). In a

Danish study, an increased risk of invasive illness has been observed with 3.5% of the patients

investigated being hospitalized. An increased mortality was recorded in 1.2% of the patients in up

to two years after the infection. In both cases the infections were associated with quinolone or

multi-drug resistant �� Typhimurium (Helms � ��., 2002; Helms � ��., 2004).

Recently, multi-drug resistant NTS have increased and have reached an alarming level

worldwide. While the extent varies, the increased level of multi-drug resistant NTS has become a

problem in all countries. Data have revealed that countries in Southeast Asia and Africa tend to

have a high level of resistant NTS (Collard � ��., 2007; Lee � ��., 2009; Vanderberg � ��.,

2009). Several publications have described the increasing occurrence of multi-drug resistant NTS

and isolates resistant to both fluoroquinolone and 3rd generation cephalosporins in Southeast Asia

and Africa (Archambault � ��., 2006; Lauderdale � ��., 2006; Aarestrup et al., 2007; Collard � �

�., 2007; Vandenberg � ��, 2009; Lee � ��., 2009; III; IV; V). Lee � ��. recently described the

level of antimicrobial resistance from 2003 to 2005 in seven Southeast Asia countries. They

12

found that Taiwan and Thailand demonstrated an alarming high frequency of resistance to

fluoroquinolones and 3rd generation cephalosporins. These findings were also supported by

Sirichote � ��. who found cephalosporinases producing �� Choleraesuis from Thai patients and a

Danish traveler to Thailand harbouring both ��CTX-M-14 gene and ��CMY-2 gene (V). Hendriksen

� ��. showed that among 33 Thai patients infected with ��Rissen 36%, 27%, 33%, 30%, 27%,

and 88% of the isolates were resistant to ampicillin, chloramphenicol, spectinomycin,

streptomycin, sulfamethoxazole, trimethoprim, and tetracycline, respectively (III). Another study

highlights the same worrisome frequency of multi-drug resistance in children from Ethiopia (IV).

The investigation revealed that among 43 �� Concord isolates, all isolates were resistant to

ampicillin, chloramphenicol, streptomycin, sulfamethoxazole, and trimethoprim. In addition,

97%, 97%, 69%, and 14% of the isolates showed resistant or decreased susceptibility to

ceftriaxone, gentamicin, tetracycline, and ciprofloxacin, respectively. All of the isolates resistant

to ceftriaxone harboured the ��CTX-M-15 gene and 13 of the isolates also the ��SHV-12 gene (IV).

In response to worldwide increases in multi-drug resistance among human bacterial pathogens,

the WHO has developed a list ranking the critically important antimicrobials. This categorization

of antimicrobials is prioritized according to their importance in human medicine, and is intended

to help assess the risks associated with resistance (Anonymous, 2007e; Collignon � ��., 2009). In

addition, individual countries without a strict antimicrobial policy should consider lowering the

consumption of antimicrobials, ban antimicrobial growth promoters and enforce prescription-

only policies to accommodate the increasing frequency of multidrug resistant pathogens

worldwide.

�

MAIN RESERVOIRSAs a zoonotic foodborne bacterium, �� has reservoirs in various animals. The most

common domesticated animal hosts are chickens, pigs, and cattle; but many other domestic

animals as well as a wide range of wild animals can also harbour this organism. Because of the

ability of �� to contaminate meat during slaughter and to survive in fresh meats and

meat products that are not thoroughly heated, animal products constitute a main vehicle of

transmission. Another important vehicle of transmission is eggs that are contaminated on the

surface or in the interior of the egg. Finally, produce and other vegetables that are contaminated

13

with animal manure during growing or processing are increasingly recognized as an important

source of human �� infections

��

NTS have a wide range of hosts and reservoirs which mostly have been associated with

agricultural product. Some of the NTS are host adapted or host restricted while others are non-

specific and cause infections in various hosts, leading to their division into two separate groups

(Uzzau � ��., 2000; Cray � ��., 2000).

The host restricted serovars cause disease in a limited number of animal species such as ��

Abortusequi (horses), �� Gallinarum (poultry), �� Pullorum (poultry), �� Typhisuis (swine), and ��

Abortusovis (sheep). The host adapted serovars are most prevalent in one animal species, but are

also able to cause severe illness in a limited number of other hosts. These serovars include ��

Choleraesuis (predominantly in swine and human) and �� Dublin (predominantly in cattle and

human) (Uzzau � ��., 2000; Chiu � ��., 2004). There are limited data describing the reasons

these serovars only affect a limited number of hosts compared to non-specific serovars which

colonize a broad range of animals and humans (Uzzau � ��., 2000).

Some decades ago, ��Choleraesuis was in many countries one of the most predominant serovars

isolated from swine (Cray � ��., 2000). Recently, the prevalence decreased in Europe and is not

presently listed among the top serovars isolated from swine (Uzzau � ��., 2000; Anonymous,

2007f; Anonymous, 2009a; Anonymous, 2009b). In many countries, �� Choleraesuis is now

believed to be eradicated. However, the incidence in the United States does not seem to have

followed the same path as in Europe and�� Choleraesuis have not decreased to a similar level.

Thus, �� Choleraesuis represent a major swine pathogen in the United States and costs the

producers an estimated $100 million annually (Gray � ��., 1996; Uzzau � ��., 2000). Despite the

high prevalence in animals, it rarely causes human illness in the United States, with

approximately 40 cases annually (Foley � ��., 2008). Today, �� Choleraesuis is mainly a problem

in Southeast Asia, especially in Taiwan and Thailand, with high frequencies of human illness.

This may be due to little effort to prevent and control this serovar, but also as a consequence of

local small scale farming where infection control is difficult (Chiu � ��., 2004; Foley � ��., 2008;

Lee � ��., 2009; V; VI).

14

In many European countries, surveillance shows that �� Dublin is the most commonly isolated

serovar from bovine meat, exceeding the level of �� Typhimurium (Anonymous, 2009b). In 2007,

it was the most common serovar in bovine meat from both Denmark and the Netherlands with

68.2% and 63.3% of isolates, respectively. In the same year, �� Dublin was also ranked as the

most common serovar isolated from cattle herds in Austria (33.3%), Belgium (66.3%), Denmark

(52.3%), Ireland (82.5%), the Netherlands (63.6%), Sweden (34.8%), and the United Kingdom

(65.1%) among 15 European countries including Norway (Anonymous, 2009b).

It is difficult to estimate the frequency of ��Dublin among cattle isolates from outside of Europe

due to limited data. �� Dublin is not listed among the most common serovars in cattle from either

the Unites States, Canada or New Zealand (Wray � ��., 2000; Anonymous, 2007c; Anonymous,

2007d; Anonymous, 2008b).

Because the reservoirs of the host adapted serovars are known, and limited in number, countries

with a high number of human infections caused by these serovars could implement control

strategies to eradicate the serovars among the reservoir in order to limit the transmission to man.

�

��

The non-specific serovars are not restricted to a single host but able to colonize, and on occasion,

cause severe illness or gastroenteritis in a wide range of animal species (Uzzau � ��., 2000).

Today, more than 2.579 different serovars are known to man (Grimont � ��., 2007) but only a

limited number of approximately 50 serovars are predominantly found in domestic animals. The

primary reservoirs for the majority of the remaining serovars remain obscure.

Several factors complicate a clear picture of the true link between the serovars and the animal

reservoir such as the production systems (intensive / free range), irrigation (manure) and

contamination of food sources (cross contamination). In addition, only a limited number of

countries have established a systematic integrated laboratory-based surveillance system, which

includes data from both food and animals. Despite these factors, some serovars appear to be more

frequently associated with certain animal species and / or production systems than others.

In Figure 7, the most commonly isolated serovars in 2007 from pig meat in eight European

countries are illustrated (Anonymous, 2009b). Only two serovars; ��Typhimurium and �� Derby

were common for all nine countries. The same distribution of serovars was observed for pig herds

for 17 European countries. A comparison with the incidents data from the United Kingdom

15

Canada Swine, Abattoir 2007 Serovars Percentages S. Typhimurium 30.4% S. Brandenburg 5.7% S. Infantis 5.7% S. London 4.8% S. Mbandaka 3.8% S. Agona 2.9% S. California 2.9% S. Heidelberg 2.9% S. Krefeld 2.9%

Nine European countries Pig Meat 2007 Serovars PercentagesS. Typhimurium 37.6% S. Derby 21.0% S. I [1],4,[5],12:i:- 4.4% S. Infantis 4.0% S. Rissen 3.4% S. Bredeney 2.8% S. London 1.6% S. Brandenburg 1.6% S. Enteritidis 1.3%

The United States Pork Chop 2007Serovars Percentages S. Infantis 27.8% S. Derby 22.2% S. Typhimurium 16.7% S. Mbandaka 11.% S. Hadar 5.6% S. Saintpaul 5.6% S. Montevideo 5.6%

The United Kingdom Pigs, livestock 2007 Serovars PercentagesS. Typhimurium 69.7% S. Derby 7.9% S. London 3.6% S. Anatum 2.4% S. Bovismorbificans 2.4% S. Kedougou 2.4% S. Reading 1.8%

Thailand Pork 2003 Serovars PercentagesS. Anatum 36.8% S. Rissen 15.8% S. Derby 14.0% S. Corvallis 8.8% S. Stanley 7.0% S. Panama 7.0% S. Bovismorbificans 5.3% S. Kedougou 5.3%

Canada Swine, Abattoir 2007 Serovars Percentages S. Typhimurium 30.4% S. Brandenburg 5.7% S. Infantis 5.7% S. London 4.8% S. Mbandaka 3.8% S. Agona 2.9% S. California 2.9% S. Heidelberg 2.9% S. Krefeld 2.9%

Nine European countries Pig Meat 2007 Serovars PercentagesS. Typhimurium 37.6% S. Derby 21.0% S. I [1],4,[5],12:i:- 4.4% S. Infantis 4.0% S. Rissen 3.4% S. Bredeney 2.8% S. London 1.6% S. Brandenburg 1.6% S. Enteritidis 1.3%

The United States Pork Chop 2007Serovars Percentages S. Infantis 27.8% S. Derby 22.2% S. Typhimurium 16.7% S. Mbandaka 11.% S. Hadar 5.6% S. Saintpaul 5.6% S. Montevideo 5.6%

The United Kingdom Pigs, livestock 2007 Serovars PercentagesS. Typhimurium 69.7% S. Derby 7.9% S. London 3.6% S. Anatum 2.4% S. Bovismorbificans 2.4% S. Kedougou 2.4% S. Reading 1.8%

Thailand Pork 2003 Serovars PercentagesS. Anatum 36.8% S. Rissen 15.8% S. Derby 14.0% S. Corvallis 8.8% S. Stanley 7.0% S. Panama 7.0% S. Bovismorbificans 5.3% S. Kedougou 5.3%

)��3��;�� - �� -��+��1773�6��1773�6�<�� 17736��1779�6��177=�,��

reveals the same complexity in pigs (livestock). In 2007, only three of the serovars described i

the overall prevalence of pig meat from the nine European countries were listed among the top

seven serovars isolated from pigs in the United Kingdom (Anonymous, 2007f). These data

revealed that even within small geographical area huge changes may be present. Differences w

also revealed when compared with 2007 data from the United States

n

ere

and Canada (Anonymous, 2008b; Anonymous, 2007c; Anonymous, 2007d). The top three most

common serovars from pork chops in the United States were the same as observed in pig meat

from Europe (Anonymous, 2007c). However, the list revealed additional serovars when surveyed

marked hogs; �� Johannesburg (9.9%), �� Saintpaul (6.4%), �� Adelaide (4.9%), �� Agona (4.4%),

and �� Hadar (3.9%) (Anonymous, 2007c). The list was further expanded when assessing the data

from Canada from swine abattoirs (Anonymous, 2008b). In Thailand, a different set of serovars

were reported from pork isolated in 2004 (Figure 7) (Vindigni � ��., 2007). It is still unknown if

16

the huge number of serovars isolated from swine is a result of a better surveillance or if other

factors contribute to the increase of serovars (Lee � ��., 2009).

It appears as the number of different serovars associated with cattle are just as diverse as for

swine. In the European surveillance of bovine meat in 2007, three of the five countries have

reported only two to three serovars (Figure 8) (Anonymous, 2009b). Canada

In the Netherlands and Denmark, �� Dublin was the most prevalent serovar in bovine meat.

However, in Ireland and Italy numerous serovars were isolated from bovine meat thus in both

countries �� Typhimurium was the most frequent serovar observed. The distribution of serovars

in cattle herds from 15 European countries including Norway is quite different from the serovars

in bovine meat from the five European countries. The only serovars ranked similarly in cattle

herds compared to bovine meat are�� Typhimurium and �. Dublin whereas several serovars, such

)��9��;�� - �� -��+0�� 17736 ��1773�6��1773�6��1779�6��177=�,��

Bovine 2007 Serovars Percentages S. Typhimurium 32.6% S. Kentucky 21.2% S. Cerro 9.8% S. I 6,14,18:-:- 8.3% S. Thompson 4.5% S. I 4:i 3.8% S. Schwarzengrund 3.0% S. Anatum 2.3% S. Montevideo 2.3%

Five European countries Bovine Meat 2007

Country data in Percentages Serovars

Cze

ch R

ep.

Den

mar

k

Irel

and

Italy

Net

herla

nds

S. Typhimurium 38.9% 9.1% 34.3% 27.3% 9.1%S. Dublin 68.2% 20.0% 63.6%S. Enteritidis 22.2% 2.9% 5.5% 9.1%S. Derby 8.6% 9.1% S. Infantis 1.8% S. Rissen 5.7% 3.6% S. I [1],4,[5],12:i:- 5.5% S. Bredeney 5.5% S. Kentucky 8.6% S. London 16.7%

The United States Ground beef 2007 Serovars Percentages S. Montevideo 23.4% S. Dublin 9.8% S. Muenster 7.6% S. Mbandaka 6.3% S. Newport 6.0% S. Typhimuriuml 5.2% S. Cerro 4.9% S. Meleagridis 4.4% S. Agona 4.1% S. Anatum 3.8 S. Infantis 2.7% S. Kentucky 2.7%

The United Kingdom Cattle 2007 Serovars PercentagesS. Dublin 59.0% S. Typhimurium 14.3% S. Anatum 5.5% S. Mbandaka 4.2% S. Monetvideo 2.8% S. Newport 1.9% S. Agama 1.5% S. Ohio 1.0%

Tunisia Cattle 1994-2004 Serovars PercentagesS. Enteritidis 69.0% S. Amsterdam 7.7% S. Corvallis 7.0% S. Hadar 3.0% S. Anatum 2.6% S. Typhimurium 2.3% S. Livingstone 1.0% S. Infantis 0.5% S. Cerro 0.5% S. Braenderup 0.5% S. Mbandaka 0.5%

CanadaBovine 2007 Serovars Percentages S. Typhimurium 32.6% S. Kentucky 21.2% S. Cerro 9.8% S. I 6,14,18:-:- 8.3% S. Thompson 4.5% S. I 4:i 3.8% S. Schwarzengrund 3.0% S. Anatum 2.3% S. Montevideo 2.3%

Five European countries Bovine Meat 2007

Country data in Percentages Serovars

Cze

ch R

ep.

Den

mar

k

Irel

and

Italy

Net

herla

nds

S. Typhimurium 38.9% 9.1% 34.3% 27.3% 9.1%S. Dublin 68.2% 20.0% 63.6%S. Enteritidis 22.2% 2.9% 5.5% 9.1%S. Derby 8.6% 9.1% S. Infantis 1.8% S. Rissen 5.7% 3.6% S. I [1],4,[5],12:i:- 5.5% S. Bredeney 5.5% S. Kentucky 8.6% S. London 16.7%

The United States Ground beef 2007 Serovars Percentages S. Montevideo 23.4% S. Dublin 9.8% S. Muenster 7.6% S. Mbandaka 6.3% S. Newport 6.0% S. Typhimuriuml 5.2% S. Cerro 4.9% S. Meleagridis 4.4% S. Agona 4.1% S. Anatum 3.8 S. Infantis 2.7% S. Kentucky 2.7%

The United Kingdom Cattle 2007 Serovars PercentagesS. Dublin 59.0% S. Typhimurium 14.3% S. Anatum 5.5% S. Mbandaka 4.2% S. Monetvideo 2.8% S. Newport 1.9% S. Agama 1.5% S. Ohio 1.0%

Tunisia Cattle 1994-2004 Serovars PercentagesS. Enteritidis 69.0% S. Amsterdam 7.7% S. Corvallis 7.0% S. Hadar 3.0% S. Anatum 2.6% S. Typhimurium 2.3% S. Livingstone 1.0% S. Infantis 0.5% S. Cerro 0.5% S. Braenderup 0.5% S. Mbandaka 0.5%

17

as �. Anatum, �. Havana, �. Goldcoast, �. Give, �. Bovismorbificants, are not listed among the 10

most frequently isolated serovars in bovine meat (Anonymous, 2009b). The distribution of

serovars in cattle based on livestock incidents data was for the United Kingdom different from

the overall European data in 2007 (Anonymous, 2007f). In Tunisia, the prevalence of serovars in

cattle was quite different from Europe. Between 1994 to 2004, �� Enteritidis was ranked as the

most common followed by ��Amsterdam and ��Corvallis (Ben-Aissa � ��., 2007). In the United

States, �� Montevideo was the most common isolated serovar among ground beef followed by ��

Dublin (Anonymous, 2007d). �� Cerro seemed to be frequent in Canada where it was ranked as

the third most common serovar in cattle (Anonymous, 2008b).

�� Enteritidis is probably best known for its association with poultry (>��) and egg.

Today, �� Enteritidis no longer ranks among the most common serovars in chickens in many

countries and the prevalence is decreasing in both egg and chicken. In 2007, �� Kentucky was

listed as the most common serovar in broiler meat from Europe. However, this included only four

(Austria, Czech Republic, Ireland, and Slovakia) out of 11 countries. All of the 11 countries in

the European survey have ranked��Enteritidis second (Figure 9) (Anonymous, 2009b). In 2007,

��Enteritidis is still ranked as the most common serovar isolated from flocks of >��

among 14 European countries with exception of Germany where�� Livingstone is the most

predominant serovar. Interestingly, a comparison of predominant serovars between chicken meat

(>��, and flocks of >�� among European countries reveal some differences in

the ranking of serovars shared by both reservoirs. In addition, frequently isolated serovars present

in chicken meat such as �. Kentucky, �. Agona, �� Ohio, and �. Indiana are not ranked among the

10 most common serovars in flocks of >�� whereas the opposite is the case with �.

Livingstone, �. Mbandaka, �. Seftenberg, and �. Bredeney (Anonymous, 2009b). In the United

Kingdom, additional serovars were observed being highly frequent mong chickens in 2007

(Anonymous, 2007f). The same tendency of �� Enteritidis decreasing was observed in 2007

among broilers in the United States (Anonymous, 2007d). The exact same pattern as observed in

the United States was seen in Canada where the same two serovars were listed first and second

with approximately the same percentages (Figure 9) (Anonymous, 2008b). There is a need to

regularly survey the primary animal reservoirs in order to detect the emergence of new and

emerging serovars or sub-types such as for instance �� Typhimurium DT 104, to elucidate their

epidemiology, and epidemic potential, and to conduct targeted interventions to avoid

18

19

The United States Broiler 2007 Serovars PercentagesS. Kentucky 47.1% S. Heidelberg 13.4% S. Enteritidis 10.8% S. Typhimurium 9.0% S. I [1],4,[5],12:i:- 4.6% S.Montevideo 2.2% S. Berta 1.5% S. Infantis 1.5% S. Mbandaka 1.1%

Canada Chicken 2007 Serovars PercentagesS. Kentucky 43.1% S. Heidelberg 17.8% S. Enteritidis 9.9% S. Hadar 5.0% S. I 4:i 3.5% S. Kiambu 3.0% S. Typhimurium 3.0%

The United Kingdom Chicken 2007 Serovars PercentagesS. Enteritidis 18.8% S. Livingstone 13.0% S. Senftenberg 8.9% S. Agama 8.3% S. Kedougou 7.3% S. Mbandaka 7.3% S. Gallinarum 3.1% S. Typhimurium 3.1% S. Ohio 3.1%

Canada

Eleven European countries Broiler Meat 2007 Serovars PercentagesS. Kentucky 17.5% S. Enteritidis 16.5% S. Paratyphi B (Java) 10.2% S. Typhimurium 7.2% S. Infantis 7.0% S. Hadar 4.7% S. Virchow 4.6% S. Agona 3.3% S. Ohio 1.9% S. Indiana 1.8%

The United States Broiler 2007 Serovars PercentagesS. Kentucky 47.1% S. Heidelberg 13.4% S. Enteritidis 10.8% S. Typhimurium 9.0% S. I [1],4,[5],12:i:- 4.6% S.Montevideo 2.2% S. Berta 1.5% S. Infantis 1.5% S. Mbandaka 1.1%

Chicken 2007 Serovars PercentagesS. Kentucky 43.1% S. Heidelberg 17.8% S. Enteritidis 9.9% S. Hadar 5.0% S. I 4:i 3.5% S. Kiambu 3.0% S. Typhimurium 3.0%

The United Kingdom Chicken 2007 Serovars PercentagesS. Enteritidis 18.8% S. Livingstone 13.0% S. Senftenberg 8.9% S. Agama 8.3% S. Kedougou 7.3% S. Mbandaka 7.3% S. Gallinarum 3.1% S. Typhimurium 3.1% S. Ohio 3.1%

Eleven European countries Broiler Meat 2007 Serovars PercentagesS. Kentucky 17.5% S. Enteritidis 16.5% S. Paratyphi B (Java) 10.2% S. Typhimurium 7.2% S. Infantis 7.0% S. Hadar 4.7% S. Virchow 4.6% S. Agona 3.3% S. Ohio 1.9% S. Indiana 1.8%

transmission to humans if necessary. In some countries, the primary animal reservoir might not

be cattle, swine or poultry but reptiles or seafood. Several studies have shown that reptiles are

reservoirs for �� that are able to affect humans (Cooke � ��., 2009; Pedersen � ��.,

2009). Similarly, rare serovars have been suggested to be associated with seafood (Aarestrup � �

��, 2003) and other serovars have found niches in small production settlements (Raufu � ��.,

2009).

)��=��;�� - �� -��+��1773�6��1773�6��1779�6��177=�,��

�

TRANSMISSION – LOCAL AND GLOBAL ��

The primary reservoirs of NTS are the intestinal tracts of colonised food- and wild animals. In

most industrialised countries, food of animal origin is the primary vehicle for human

salmonellosis, however multiple routes of transmission has been documented including vector-

and waterborne, animal-, human- and environmental contact, as well as many others. In the

Netherlands, �� Typhimurium isolated from a pig, a calf, and a child on a farm were identical,

indicating animal-to-animal and animal-to-human transmission (Hendriksen � ��., 2004).

�� is passed on from the intestinal tract of the host to meat products during slaughter,

where faecal contamination often occurs. Human infections are acquired from contaminated

meats due to inadequate cooking or poor kitchen hygiene, the latter of which can result in cross-

contamination of uncooked foods such as vegetables (Figure 10).

)��*7�� -�� -��

20

In 2007, 26.3% of human infections in Denmark were associated with domestically produced

meat products, 11.7% were associated with imported meat, and 48.2% were associated with

international travel (Anonymous, 2009a). Waste/manure from the production of food animals or

from abattoirs often contains ��, which can survive for years outside its host in the

environment, sewage, or slurry tanks. Faecally contaminated water from these reservoirs is a

major route of ��

transmission to vegetables and fruits,

and can results in human infections.

The increased demand from

consumers for fresh vegetables and

fruits year round has also resulted in

an increased level of NTS outbreaks

caused by these commodities.

Several environmental factors

contribute to produce contamination

by NTS, such as irrigation and rinse

of the crops in polluted fresh and

waste water, some of which originated from animal production systems (Figure 11)

(Sivapalasingam � ��., 2003; Hanning � ��., 2009). A recent review highlights examples of

human outbreaks in the United States from 1950 to 2007 associated with vegetables and fruits. At

least 25 different NTS in at least 15 different vegetable or fruit products were responsible for the

outbreaks in this time period (Hanning � ��., 2009). In 2004, an international outbreak associated

with imported Italian rucola letters occurred in Sweden, Norway, and the United Kingdom

(Nygård � ��., 2008). This outbreak was caused by �� Thompson and resulted in 21 reported

cases, but was believed to be much larger in magnitude. In 2008, a multi-state outbreak in the

United States was caused by �� Saintpaul. A total of 1.442 persons from 43 states in the United

States and Canada were infected, 286 of which were hospitalized and two died. The responsible

vehicle was jalapeño peppers imported from Mexico, but Serrano peppers and tomatoes also were

believed to have contributed to the outbreak. All of these products were contaminated with

�� from irrigation water polluted by an animal source (Anonymous, 2008f). A large

)��**�� $��

21

number of �� infections caused by contaminated vegetables or inadequate cooking could

probably be prevented if consumers followed basic kitchen hygiene regimes, such as frequent

hand washing, thorough cleaning of raw vegetables, keeping hot items hot and cold items cold,

and by the separation of raw meat and vegetables on the cutting board.

�

��

Recently, several countries have initiated the development of systems to attribute sporadic cases

of human salmonellosis to specific sources, in the quest to control and prevent salmonellosis.

In Denmark, a source attribution model was applied to retrospectively assess sources of

salmonellosis between

1988 and 2004. In 2000

to 2001, 53.1% of all

cases were linked to

domestically produced

food products – mainly

table eggs (37.6%).

However, the data also

showed that 19% of all

cases were travel

related and 9.5% were

associated with

imported food products – dominated by chickens (Hald � ��., 2007). In 2007, the travel

associated cases increased considerably to 46% of all cases compared to the 2001 data, due in

part to a substantial improvement in reporting travel information, and in part to a reduction in the

number of domestically acquired infections (Anonymous, 2009a). Consequently, the infections

acquired from domestically produced food items decreased to 19% in 2007. Similarly, a

reduction in �� cases that could be attributed to imported food products was observed in

the 2007 data due to a huge decrease in the number of cases associated to imported chickens,

probably due to enhanced control of imported food products. The overall results of the Danish

source attribution system revealed that travel associated sources and imported food products were

far more important risk factors of human �� infections than was consumption of

Travel (44.4-48.2%)

Unknown (20.0-26.8%)

Outbreak, source unknown (4.6%)

Pork (3.6-9.7%)

Chicken (0.1-1.8%)

Beef (0.2-1.6%)

Layers (8.9-13.2%)

Imported turkey (1.2-1.8%) Imported chicken (2.1-

5.3%)

Imported beef (0.6-1.8%)

Imported pork (0.2-2.8%)

)��*2��'� �� *�843�� /��1773��"�/��?��$�� @� ��)�� A�� /��

22

domestically produced products in 2007 (Figure 13) (Anonymous, 2009a). Countries with

integrated laboratory-based surveillance systems could benefit from attributing the human

infections to specific food categories, and other sources, and by this approach, gain knowledge

that can enable them to target control, intervention, and prevention strategies to the most

important sources.

� ��

Danish pigs

Suscep100%

Resis0%

Danish Patients

Suscep43%

Resistant57%

Chicken meat in ThailandSuscep11%

Resistant89%

Thai patientsSuscep

9%

Resistante

Chicken meat in DenmarkSuscep18%

Resistant82%

In the last decade, the international trade of food has increased resulting in increasing import of

cheaper food products from countries with little or no control programmes of foodborne

pathogens. In addition, many of the imported food products contain multi-drug resistant

foodborne pathogens (Aarestrup � ��., 2007). Today, international trade of food products

contaminated with not only NTS but all foodborne pathogens poses a threat to the public health.

A retrospective study investigated the association between imported pig and pork from Germany

and Spain and Thai food products and Thai patients with Danish patients all containing or

infected with �� Rissen (I). The data revealed that six out of nine isolates from imported pork had

the same genetic Pulsed

Field Gel Electrophoresis

(PFGE) pattern as a Danish

patient. Aarestrup � ��

described the spread of ��

Schwarzengrund resistant to

nalidixic acid from

imported Thai chicken to

Denmark (Figure 12). The

data showed that ��

Schwarzengrund from

Danish pigs were

susceptible to nalidixic acid,

in contrast to isolates from

the Thai chicken. However, Danish patients were infected with both nalidixic acid resistant and

susceptible �� Schwarzengrund isolates, suggesting that Danish patients were affected by

International travel

)��*1�� -��(�� /�� A� �� $�� )��%��

23

consumption of Thai chickens imported to Denmark or consumed in Thailand, and domestically

produced pigs (Aarestrup � ��., 2007).

The import of live animals is a means by which NTS can disseminate between countries. In 2003,

the first case of NTS resistant to extended spectrum cephalosporins (ESC) occurred in a pig

intended for breeding, which was imported into Denmark from Canada (Aarestrup � ��., 2004).

Microbiological study of the intestinal contents of this animal revealed the presence of a ��

Heidelberg strain harboring the ��CMY-2 gene. While rare or absent in most regions of the globe,

�� Heidelberg ranks amongst the most prevalent causes of human salmonellosis in Canada and

the United States. In addition, an increase in ESC resistance has been observed both by the

Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) (Andrysiak � �

�., 2008) and the U.S. National Antimicrobial Resistance Monitoring System (NARMS) (Folster

� ��., 2009).

�� infections caused by imported food and food animals represent an increasingly

important cause of human infections in some countries, highlighting the need for better import

control and testing. The approach could help limit the number of human infections, but result in

considerable challenges for exporting countries and eventually limited the volume of infected

food products.

� ��

In 2004, global travel reached a record of 763 million arrivals, an increase of 11% compared to

2003 (www.world-tourism.org). The increase was observed in all regions but was most profound

in Asia (28%) and the Middle East (18%). The intensity of international travel is a public health

concern since an increasing number of travellers return home with mild or severe infections

(Archambault �� ., 2006; III; V). In 2008, 3,022 confirmed human salmonellosis cases were

reported to Statens Serum Institute. Of these, 706 (23.3%) were confirmed to be travel associated

and 95 (13.4%) of these cases were linked to travelling to Thailand (unpublished data). In the

same year, 149.570 Danes visited Thailand (http://www.tourism.go.th/). The number of infected

Danes returning back from Thailand might be underestimated and may have been 10-20 times

higher (Wheeler � ��., 1999). Taking this underestimation into consideration, 0.6% of the Danes

visiting Thailand may have brought back a �� infection in 2008 (V). The Swedish

database on notifiable communicable diseases identified 24.803 NTS cases associated with

24

international travel from 1997 to 2003. High risk of disease was seen in travellers returning from

Africa, India, and Southeast Asia (Ekdahl � ��., 2004).

Three recent studies have linked Danish patients, suffering from either gastrointestinal infections

or bacteremia, with travel to Thailand (Archambault � �� ., 2006; III; V). One investigation

linked six �� Rissen isolates recovered from Danish patients with travel to Thailand, where

genetically identical �� Rissen isolates were found. In addition, several of the isolates shared the

same phenotypic and genotypic antimicrobial susceptibility patterns (III). Similarly, sporadic

cases of travel associated salmonellosis have been frequently described (Collard � �� .; 2007;

Kasper � ��.; 2009). Recently, an outbreak of travel associated �� Enteritidis illness was detected

in Finland. Petrov � ��. linked Finnish outbreak strains with strains from Sunny Beach, Bulgaria

where employees at a hotel were also infected. The outbreak likely included tourists from the

United Kingdom, Norway, Sweden, and Germany (Petrov � ��., 2009).

Multiple studies have revealed that international travel to certain destinations is associated with a

relatively high risk of human salmonellosis. However, little has been done to avoid it. The best

way to prevent it is ensure an adequate level of food safety globally, and by educating the general

population about food borne disease prevention under different circumstances.

� ��

The international adoption of children carrying and transmitting infectious diseases is probably a

minor but clearly an overlooked problem. Since 1986, nearly 220.000 children have been adopted

by North American families (Miller � ��., 2005). In 2007, the most common countries of origin

for Danish adoptions were China, Vietnam, South Africa and Ethiopia. For U.S. adoptions, most

were from China, Guatemala, Russia and Ethiopia (IV). Today, international adoption medicine

is a relatively new specialization in paediatrics that has emerged to address the specific health

care needs of children and their adoptive families (Miller � ��., 2005). Common infectious

diseases in adopted children include tuberculosis, hepatitis B and C, HIV, syphilis, parasites and

enteric infectious diseases (Miller � ��., 2005). In 1997 and 1998, a study determined the

prevalence of infectious diseases among 504 adoptees. The data revealed that 90% of the stools

were abnormal and that two of the children carried a �� species (Saiman � ��., 2001).

25

In France, fourteen �� Babelsberg harbouring the ��SHV-12-like gene and six �� Enteritidis isolates

were detected in 2002 and 2003 from international adoptees. All of the children were traced back

to one orphanage in Mali (Weill � ��., 2004).

Figure A

0

200

400

600

800

1000

1200

1400

1

Num

ber o

f Eth

iopi

an a

dopt

ees The United States

Europe

Figure B

0

5

10

15

20

25

30

2003 2004 2005 2006 2007

Num

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f Salmonella

Con

cord

isol

ates

iden

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The United StatesEurope

In 2007, infections caused by �� Concord were reported in several countries among children

adopted from Ethiopia. A total of 3.419 children were adopted from Ethiopia from 2003 to 2007

and brought to Denmark, England and

Wales, Ireland, the Netherlands and the

United States.

During this period, the number of children

adopted from Ethiopia increased from 221

adoptions in 2003 to 1.385 in 2007. The

five countries including Austria reported

78 laboratory confirmed cases of ��

Concord from 2003 to 2007 (Figure 14)

(IV). Simultaneously, another study

reported 35 French and 27 Norwegian

cases of �� Concord of which 28 and 26,

respectively, originated in children from

Ethiopia (Fabre � ��., 2009). In a study

by Hendriksen � ��. where adoption

status was known for 44 (79%) of the

patients � 3 years of age, 43 were adopted from Ethiopia. One patient � 3 years of age and two

patients �18 years of age were either a sibling or mothers to Ethiopia adoptees (IV). Six adoptees

were asymptomatic at the time of adoption. In addition, the data showed that among 35 isolates,

all from or associated with a child adopted from Ethiopia, were multi-drug resistant including

resistance to third generation cephalosporins. Six (14%) also showed reduced susceptibility to

ciprofloxacin. All of the 35 isolates harbored the ��CTX-M-15 gene and 17 of them also the ��SHV-

12 gene. Of the six ciprofloxacin resistant isolates three harbored a B�� gene (IV).This work

indicates the need for mandatory screening of adoptees, not only for foodborne pathogens but

also for viruses and parasites, for the benefit of the children and respectively new families. In

)��*4��@�� ' ��+��,�� $��+��0,��'�� A� �� 1772�1773�+IV,��

26

addition, the findings should be disseminated to the orphanages along with assistance to resolve

the problem of infections.

SURVEILLANCE��

Surveillance is defined by the WHO as a systematic ongoing collection, collation, analysis, and

interpretation of data and a timely

dissemination of information to those

who need to know so that public health

actions can be taken (Figure 15).

Surveillance is conducted to facilitate a

better control of diseases and lead to

public health actions such as outbreak

detection, to measure the magnitude, the

burden, and trends of disease, to

improve the knowledge of the disease (causes, sources, reservoirs, risks, morbidity, and

mortality), guide programmes to measure the effectiveness of interventions, and to assist

policymakers in setting priorities. To date, four generic types of enteric disease surveillance

systems exist; no formal (occasional) surveillance, syndromic surveillance, laboratory-based

surveillance, and integrated laboratory-based surveillance. The last two types are mostly

associated with foodborne pathogens and stand out from the first two types of surveillance

systems by being based on laboratory results. Integrated foodborne surveillance refers to

concomitant testing of isolates from humans, animals and foods, and may include environmental

and animal feed samples.

)��*:�� -�� C��)��D��/%�� "��1774��

Surveillance of NTS infections in humans is conducted in a hierarchical structure from local to

global. Since 2000, the WHO has volunteered to collect data and facilitate a global surveillance

of �� by establishing the CDB. Global surveillance is relative important as it render

analysis of the major trends worldwide limiting the influence of local outbreaks and other

elements which complicate interpretation (II, Galanis � ��., 2006). Ongoing overall trend

analysis may provide crucial knowledge of emerging serovars on global level which might result

27

in pandemic proportions and millions of cases or pin out regional endemic serovars. In addition,

global surveillance may also identify problems of global importance which may be difficult to

detect due to the limitations in national surveillance such as occurrences of important rare

serovars in low frequencies present in several countries (IV). Regional or national surveillance

are mostly governed by the individual countries and conducted by national or regional public

health institutes. Regional or national surveillance allows the scientists to narrow the focus on

specific national emerging or rare serovars. The focus offers the opportunity to initiate detailed

epidemiological and molecular studies and set priorities for intervention strategies and elucidate

associated risk factors (III, V, VI, Bangtrakulnonth � ��., 2004, Archambault ��., 2006,

Tapalski � ��., 2007, Petrov � ��., 2009). Local surveillance is often restricted to a confined

geographical area such as a large city compared to rural areas. This often results in detection of

local minor outbreaks.

�

��

In the last decade, our ability to distinguish in a rapid and reliable way between

epidemiologically unrelated isolates from the same bacterial species has increased, thereby

enhancing our capacity to detect outbreaks, conduct surveillance and understand or elucidate the

epidemiology of certain types or clones. Thus, bacterial typing techniques have been developed

to measure genetic relatedness among emerging pathogenic strains, clones or clusters of bacteria

from a single species.

In the beginning of the bacterial typing era, typing systems were based solely on phenotypic

methods such as serotyping (Grimont � ��., 2007), phage typing (Smith � ��., 1951; Guinee and

Scholtens, 1967; Sechter and Gerichter, 1968; Petrow � ��., 1974; Rowe � ��., 1980; Tyc � ��.,

1980; Scarlata � ��., 1982; Sharma � ��., 1984; Sood and Basu, 1984; Ward � ��., 1987)

and antibiogram typing (Figure 16). These methods are currently in use in many countries as part

of national surveillance programmes. The results obtained by these phenotypic tests, particularly

serotyping, have been the basis for the elucidation of the epidemiology of NTS for decades. In

addition, conventional serotyping and antimicrobial susceptibility testing are excellent

surveillance tools and also used as first line methods in outbreak detection caused by NTS.

Recently, several DNA fingerprinting and array techniques have been developed serving as an

alternative to the conventional serotyping method (McQuiston � ��., 2004; Fitzgerald � ��.,

28

2007). By merging these two

methods one should be able to

identify the major serotypes

(McQuiston � ��., 2004). The

method has proved its worth in

the characterization of a

monophasic variant of ��

Goettingen where conventional

serotyping was insufficient

(Petrov � ��., 2009).

Phenotypic methods may not have sufficient discriminatory power in an outbreak situation, and

may need to be supplemented with molecular techniques such as PFGE (Raufu � ��., 2009; III;

IV; V). The number of genotyping methods and their discriminatory power has increased and

several methods have been implemented to meet public health needs. The most commonly used

genotyping method for surveillance and outbreak detections is PFGE (Tenover � ��., 1995; Ribot

� ��., 2006; van Belkum � ��., 2007), however Multi Locus Sequence Typing (MLST) and

Multiple Locus Variable Number Tandom Repeat Analysis (MLVA) (Lindstedt � ��., 2003;

Tapalski � ��., 2007; van Belkum � ��., 2007; Lindstedt � ��., 2008) are also commonly used. In

the near future, these methods will likely be superceded by microarray technologies and full

genome sequencing (Maslow � ��., 1993; Foxman � ��., 2005; van Belkum � ��., 2007).

Since 1984, PFGE has been standardized for �� testing, allowing comparison of patterns

between laboratories around the world (Ribot � ��., 2006). Similarity indexes have partly

replaced the criteria by Tenover � �

�� by implementation of the

BioNumerics software (Applied

Maths, Sint-Martens-Latem,

Belgium) for interpretation of the

PFGE profiles. In the United States,

the preferred subtyping method is

currently PFGE used by PulseNet

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SSeerroottyyppiinngg

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29

USA for outbreak detection (Gerner-Smidt � ��., 2006) and it has also shown to be useful in

epidemiological studies of NTS worldwide (III; IV; V).

Scientists in PulseNet USA are currently developing a MLVA scheme for both �. Typhimurium

and �� Enteritidis. The strategy is to first integrate these new methods into the PulseNet platform

to complement PFGE data (Gerner-Smidt � ��., 2006). There is still a need for a common MLVA

nomenclature in order to compare results among laboratories. However, a recent publication

proposes such a nomenclature that is independent of equipment and primers used (Larsson � ��.,

2009). Before applying a typing technique, it is important to understand and evaluate the

strengths and weaknesses of the methods. Certain criteria are normally used to assess this such as

the discriminatory power,

reproducibility, typeability,

and repeatability (Figure 17).

��*��$� �� B��

A good typing method should

give the same result each time

tested in the same laboratory

(repeatability) but also when

tested in different

laboratories (reproducibility). Typically, sequence-based methods are more repeatable and

reproducible than gel based methods (Table 1). At the same time the methods should be able to

assign a specific type to all tested isolates (typeability) and furthermore, be able to assign a

different type to two epidemiologically unrelated isolates sampled randomly from a population of

the same bacterial species (discriminatory power) (Foxman � ��., 2005; van Belkum � ��.,

2007). In addition, several other aspects also affect the choice of typing techniques such as the

costs, accessibility, and workload.

Typing technique Discriminating power

Repeatability Reproducibility Comment

Whole genome sequencing Very High High Medium / High

MLST Medium / High High Medium / High Depends on gene choice

MLVA High High High

PFGE Medium / High Medium Medium

Depends on type and number of enzyme used.

Conventional serotyping Medium Medium Medium

��

In February 1997, a global survey of the 191 WHO member states was initiated to estimate the

number of countries conducting public health surveillance of ��. Only 76 (73%) of 104

countries reported conducting �� surveillance ranging from all countries in Europe to

40% of the countries in the Western Pacific region. A total of 69 countries among the 76

countries conducting surveillance of �� included serotyping (Herikstad � ��., 2002).

30

This number is quite low considering that �� in many countries is either the first or

second most common foodborne bacterial pathogen.

Despite the low number of countries conducting surveillance based on serotyping, some countries

have a long tradition for �� surveillance or have recently initiated the programmes. One

of the countries that stand out as having conducted laboratory-based surveillance for at least 15

years is Thailand. Each year, the National Institute of Health publishes an annual report of

laboratory-confirmed �� and �� in Thailand (Bangtrakulnonth � ��., 2006). This is

one among many reasons why many international �� studies have been based on or

included Thai data (Bangtrakulnonth � ��., 2004; Archambault � ��., 2006; Aarestrup � ��.,

2007; Vindigni � ��., 2007; III; V; VI). In addition to the Thai program, several other countries

conduct annual �� surveillance including New Zealand (Anonymous, 2008a), South

Africa (Anonymous, 2008c), the United States (Anonymous, 2008e), Canada (Anonymous,

2008b), Korea, Denmark, Norway, and Sweden.

In the United States, several institutes independently conduct �� surveillance in humans,

food and animals (Jones � ��., 2007). The Centers for Disease Control and Prevention (CDC)

collect data on reported laboratory confirmed �� cases of human origin to the National

�� Surveillance System (NSSS) through the Public Health Laboratory Information

System (PHLIS). The PHLIS database contains data from all state and territorial public health

laboratories (Anonymous, 2008e). The United States Department of Agriculture, Food and Safety

Inspection Service (USDA-FSIS) and the United States Food and Drug Administration Center for

Veterinary Medicine (FDA-CVM) collect �� data from food animals and retail meats,

respectively.

Integrated laboratory-based �� surveillance systems are established in a small number of

countries such as the United Kingdom (Anonymous, 2007f), Australia (OzFoodNet Working

Group, 2003), and Denmark (Anonymous, 2009a). In the United States, the surveillance in

humans is from all 50 states in contrast to animals, which are from all federally inspected

abattoirs (Jones � ��., 2007). However, in Canada an integrated surveillance programme for

antimicrobial resistance has been established (Anonymous, 2008b) which also includes serovar

distribution.

In contrast, only a few developing countries have a �� surveillance system implemented

and none of these systematically integrates data from humans, food, and animals.

31

In developing countries, information on foodborne pathogens is limited due to several factors

such as patients who do not seek medical care, samples that are not processed and/or reported

data to central public health institutes. In Mexico, syndromic surveillance was replaced in 2002

by an integrated laboratory-based surveillance system in four states. The sampling scheme was

designed to follow the food chain in a temporal mode. In a test week, food animal intestines were

collected on the first sampling day, followed by raw retail meats on the second to the fourth day.

From day 7 to 14, fecal samples from asymptomatic children were collected. This surveillance

revealed high rates of contaminated meat and ceftriaxone resistant salmonellae. Genotyping data

showed 14 PFGE clusters with indistinguishable patterns associated with human, retail meat, and

food animals (Zaidi � ��., 2008). This approach could be technical feasible for many developing

countries for future surveillance efforts. Unfortunately, it is too expensive why the described

study is currently not operating.

One could wish that WHO had the power and authority to strengthen through Codex

Alimentarius mandatory laboratory-based surveillance of foodborne pathogens in food animals,

food and humans in order to gain detailed data for initiating action to prevent human

salmonellosis.

��

In 2003, the European Parliament and Council, adopted; Directive 2003/99/EC on the monitoring

of zoonoses and zoonotic agents (Anonymous, 2003a; O’Brien et al., 2005) amending Decision

90/424/EEC (Anonymous, 1990) and repealing Council Directive 92/117/EEC (Anonymous,

1992). The purpose of the Directive 2003/99/EC was, among other things, to ensure a proper and

harmonised surveillance of zoonoses including ��. The Directive was supplemented later

the same years with the Regulation 2160/2003 on the control of �� and other specified

foodborne zoonotic agents, which in principle should cover the whole food chain, from farm to

table (breeding flocks of Gallus gallus, laying hens, broilers, turkeys, herds of slaughter, pigs,

breeding herds of pigs) (Anonymous, 2003b; O’Brien � ��., 2005). The sampling should take

place over a three year period with the possibility of extension. The surveillance should take

place on a harmonised basis by all member states according the detailed rules laid down in the

regulation. In addition, all national reference laboratories should participate in proficiency testing

arranged by the Community Reference Laboratory (CRL) to insure a high quality of the results

32

1

6

7

89

10 11

2

34

5

1

2

34

5

6

7

8

910 11

1

2

34

5

6

7

8

910 12

1

2

3

4

5

6

8

9

1314 16

1

2

3

4

5

6

910 11 15

8

submitted. The data are

complied and published

annually by the European

Food Safety Authority

(EFSA) (Anonymous,

2009b) including human

data collected by European

Centre for Disease

Prevention and Control

(ECDC) and through the

European Surveillance

System.

Others (1)S. Enteritidis (2)S. Stanley (3)S. Weltevreden (4)S. Rissen (5)S. I 4, 12:i:- (6)S. Choleraesuis (7)S. Anatum (8)S. Typhimurium (9)S. Corvallis (10)S. Panama (11)S. Kedougou (12)S. Hvittingfoss (13)S. Derby (14)S. Albany (15)S. Virchow (16)

The experience from the

European Union has

proven how important it is

to design the surveillance

program to include as

many of the countries and

the population as possible and to ensure a high quality of the data. Nevertheless, the overall

serovar distribution and frequencies in the EFSA report does not necessarily reflect the

distribution of serovars in a single country. Several studies have shown large differences in the

distribution of NTS�between countries but also among regions within a country (V; VI).

Hendriksen � ��. revealed that the serovar distribution varied considerably among five regions

within Thailand as 15 serovars were listed among the top 10 most common serovars in the

regions (Figure 18). In Thailand, the distribution of serovars seemed to be culturally linked, and

was for instance influenced by differences in pork and poultry consumption between the

Buddhist North and the Muslim population in Southern Thailand (VI).

)��*9��/� �� 1771��1773��+VI,�

In Thailand, a large amount of data has been generated, but it is not easily accessible.

Nevertheless, harmonizing surveillance programmes will in the future be of high priority in order

to have comparable data on occurrence and frequencies between countries and regions, and to

33

facilitate joint actions directed towards the most important sources of human infections in a

region or country.

!� ��

Sporadic cases and outbreaks caused by NTS is often linked to consumption of meat, egg and

recently also to contaminated fruits and vegetables (Nygård � ��., 2008; Hanning � ��., 2009). In

the United States, 121 �� outbreaks were recorded to the CDC Foodborne Outbreak

Reporting System in 2006. The outbreak consisted of more than 3.300 cases and the most

common serovars responsible for the outbreaks were �� Enteritidis (n=26), �� Typhimurium

(n=26), �� Newport (n=10), and �� Heidelberg (n=10) (Anonymous, 2008e). In comparison, there

were in 2007 observed six outbreaks caused by �� which accounted for 12% of all

outbreaks in Denmark. The serovars involved in these outbreaks were �� Typhimurium (n=27), �.

Weltevreden (n=19), �. Heidelberg (n=13), �� Enteritidis (n=9), and ��Senftenberg (n=3)

(Anonymous, 2009a). In 2007, a total of 2.201 outbreaks were reported in 22 European countries

ranging from five in Ireland and Romania to 843 in Germany.��. Enteritidis was by far the most

common serovar responsible for the outbreaks (n=355) infecting 5.940 humans. The second most

common serovar was �. Typhimurium with 63 outbreak (Anonnymous, 2009d).

In recognition that infections, including outbreaks, may originate in different countries, the Salm-

net project was established in 1993 under the leadership of the Health Protection Agency (HPA).

A main goal of Salm-net was to harmonise the �� phage typing schemes used in Europe

(Fisher � ��., 2004; Hald � ��., 2004). Participants in the Salm-net project were public health

reference laboratories in the European Union, Norway, Switzerland, Australia, Canada, Japan,

and South Africa. Salm-gene, another European network established by HPA, began in 2001 to

build a database based for �� PFGE profiles among European countries. By the end of

2004, the Salm-gene database contained approximately 20.000 profiles of primarily �� Enteritidis

and �� Typhimurium (Swaminathan � ��., 2006). In 2004, the Salm-gene network merged with

Enter-Net which later became PulseNet Europe in 2004 (O’Brien � ��., 2005; Fisher � ��.,

2005).

In the United States, PulseNet USA was established in 1996 as the national molecular

surveillance network for foodborne infections (Gerner-Smidt � ��., 2006). The aim of the

network was to rapidly detect outbreaks caused by foodborne pathogens by the use of the PFGE.

34

In 2001, full national participation by all 50 states was achieved. By 2005 the network consisted

of 65 participating public health laboratories, four countries, three cities and eight food safety

regulatory laboratories. All PFGE profiles are uploaded to the national database where local or

multi-state outbreaks are investigated. In 1999, PulseNet USA harmonised protocols with

PulseNet Canada forming PulseNet International (Swaminathan � ��., 2006). PulseNet USA and

PulseNet Canada have investigated numerous multi-national outbreaks, showing the advantage of

international collaboration in food safety surveillance. In addition to PulseNet USA and PulseNet

Canada, PulseNet networks have been established in the Asia Pacific region, Latin America,

Europe, and China. Surveillance by PulseNet Europe ceased in 2007 due to lack of funding, but

it is expected that funding from the ECDC will resume in 2010.

CONTROL, INTERVENTION, AND PREVENTION ��

Surveillance of NTS is not only about collecting data, but also analyzing the data to identify

critical points of intervention. Many types of analyses are possible. Case control studies to

identify risk factors can be sufficient to focus interventions and prevention measurements. Source

attribution modelling can provide detailed information about the nature and magnitude of

different reservoirs contributing to infection. Source attribution is partitioning of the human

disease burden of one or more foodborne infections to specific sources, guiding authorities to

prioritise intervention and control efforts and measuring the impact (Pires � ��., 2009). Several

factors need to be known to attribute burden to specific sources. A laboratory-based surveillance

system must be in place, and the burden of illness determined. In addition, the proportion of

foodborne disease due to international travel should be estimated and food items categorised. In

2004, a Danish mathematical model was published for quantifying the number of domestic and

sporadic cases caused by different serovars and phage types as a function of the prevalence of the

same serovars in each major animal or food sources (Hald � ��., 2004). In the following years,

the model was enhanced to include information on antimicrobial susceptibility. Using this model,

researchers in Denmark were able to quantify the contribution of various animals, foods, and

international travel to human infections with resistant NTS�(Hald � ��., 2007). In the United

States, the Foodborne Diseases Active Surveillance Network (FoodNet) adopted the same model

to attribute the human �� cases to various sources (Gerner-Smidt � ��., 2006).

35

��

Denmark has one of the best national programs in the world for controlling and preventing

��, and other nations look to Denmark for leadership in this area. In the 1980s, the

incidence of salmonellosis in Denmark steadily increased, and was linked to the consumption of

broiler chicken and pork. This led to a targeted national control programme (Wegener � ��.,

2003; Mousing � ��., 1997) based on the general prevention strategy known as Hazard Analysis

and Critical Control Points (HACCP). HACCP is a systematic preventive approach to food safety

that addresses physical, chemical and biological hazards as a means of prevention, rather than

finished product inspections. The HACCP strategy is to identify key steps (critical control points)

in the chain from farm to fork (Busani � ��., 2006) where interventions will have the most impact

in reducing or eliminating food safety hazards.

In 1995, the most extensive nation-wide control programme ever attempted was launched in

Danish finishing swine herds. All swine herds were tested and categorized based on their

�� prevalence. Herds were assigned to three categories: herds with low and acceptable

prevalence, moderate prevalence, and clearly unsatisfactory prevalence (Wegener � ��., 2003).

Swine herds belonging to the unsatisfactory category were slaughtered using special hygienic

precautions according to the inherent risk. In 2001, the classification scheme was extended to

include a fourth category, namely, herds being negative in serological tests (Alban � ��., 2002).

A similar approach was implemented for poultry. All shell eggs from layer flocks should be free

from ��

Enteritidis and ��

Typhimurium,

and suspected or

confirmed

positive eggs

should be

pasteurized prior

to marketing. In

addition, )��*=��/��*=99� ��1773��"�/��?��$�� @� ��)�� A�� /��

0,0

20,0

40,0

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88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07

Estim

ated

no.

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ases

per

100

,000

Broilers Pork Table eggs Total cases

0,0

20,0

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ated

no.

of c

ases

per

100

,000

Broilers Pork Table eggs Total cases

36

infected flocks either were eliminated or slaughtered separately or late in the day to avoid cross-

contamination (Wegener � ��., 2003; Hald � ��., 2005). These control programmes and targeted

interventions resulted in a major reduction in the incidence of human salmonellosis in Denmark.

The broiler, pork, and egg associated salmonellosis incidences were reduced by 95% (1988 to

2001), 85% (1993 to 2001), and 75% (1997 to 2001), respectively (Figure 19) (Wegener � ��.,

2003). The benefit of implementing the control programmes by eliminating infected animals and

diversifying slaughter were estimated to save the taxpayers in Denmark $25.5 million annually.

In 2003, the European Parliament and Council issued, in combination with the harmonised

surveillance system, Regulation 2160 on the control of �� and other specified food-

borne zoonotic agents. This regulation was intented to control �� and other specified

foodborne zoonotic agents by reducing transmission from poultry and pigs (Anonymous, 2003b).

The regulation enforced strict rules for all Member States to reduce the prevalence of ��

in primary production. The control programmes target breeding flocks of >��in 2004,

followed by laying hens, broilers, turkeys, slaughter pigs and breeding pigs over the subsequent

four years (Anonymous, 2003b).

The increased number of human infections caused by international travel is in many countries a

major concern. Currently, there is no vaccine to prevent infections caused by NTS for travellers.

Thus, in many countries, public health authorities have initiated campaigns to educate the public

on steps to reduce the risk of salmonellosis. Consumers are advised not to eat raw or

undercooked eggs, poultry or meat, not to consume raw and unpasteurised dairy products, and to

clean vegetables before consumption. The WHO instituted a similar communication programme

as part of their global strategy to decrease the burden of foodborne diseases. This lead to the

WHO report “The Five Keys to Safer Food”, which was published in 2001, and included and

associated training materials developed to provide countries with materials that are easy to use,

reproduce and adapt to different target audiences (www.who.int/foodsafety/consumer/5keys/en/).

Several publications have shown that adopted children carrying �� is an overlooked

problem (Saiman � ��., 2001; Weill � ��., 2004; Fabre � ��., 2009; IV). The American Academy

of Paediatrics recommends that a stool specimen be collected from all adopted children entering

the United States and cultured for the presence of bacterial pathogens such as ��

(Hostetter � ��., 1991; Nicholson � ��., 1992; Stauffer � ��., 2002). The utility of this

recommendation was highlighted to all countries in a study where family members were infected

37

with �� Concord which was introduced by adopted children (IV). Another approach in preventing

travel associated salmonellosis is by publishing data on the burden of salmonellosis, and routes of

transmission, in different countries. Thus, urging the country to take action to limit the sources of

infections among the general population and travelers by improving the food safety. (Aarestrup � �

�., 2007; V; VI). However, this might be a challenge due to the limited knowledge of the

epidemiology of �� in developing countries and the circumstances associated with the

production systems, which often are many small operations where animals are reared with

minimal oversight such as free range.

��

To date, only a few studies describe effective serovars-specific control programmes that do not

rely on vaccination. Multidrug resistant �. Typhimurium DT104 appeared in the 1980s and

became a major cause of salmonellosis around the world. In Denmark, a component to control

and prevent �. Typhimurium DT104 to spread and cause infections in humans was incorporated

into the existing control program for pig herds (Alban � ��., 2002). Farmers with �.

Typhimurium DT104 infected herds had to follow a herd intervention plan which included

restrictions on livestock trade and special slurry management. Carcasses of infected pigs had to

be heat treated or decontaminated before leaving the abattoir (Nielsen � ��., 2001). Likewise, a

Danish control programme for ��Dublin was launched in 2002 attempting to reduce the

increasing number of human infections and the economic losses for the cattle industry, where this

serovars was a problem. In contrast to the control programme in pigs, this programme sought to

identify cattle herds free of infection by periodic measurement of �� Dublin antibody titres in bulk

milk and by modelling the spread between herds (Hald � ��., 2005; Jordan � ��., 2008). The

outcome of the modelled control programme showed that restricting the movement of herds

between regions was more important that attempting control within herds. However, a

combination seems to be more effective but needs to be further explored (Jordan � ��., 2008).

��

To date, all attempts to develop a comprehensive vaccine for humans and animals that will cover

all important serovars of �� have failed. Today, only vaccines for humans against ��

Typhi exist. One study revealed that a Vi ��Typhi vaccine did not protect against �. Paratyphi A

38

or B since these serovars do not express the Vi polysaccharide. However, a Ty21a �� Typhi

vaccine conferred substantial cross protection against �� Paretyphi B but not to �� Paratyphi A

(Levine � ��., 2009). This example highlights the difficulties in developing �� vaccines.

A major problem is that both serovar-dependent and host-dependent factors, as well as the

attributes influencing serovar host specificity, are unknown among the more than 2.500 serovars

(Barrow � ��., 2007). Some success has been seen with �. Enteritidis, which is associated with

chickens and is mainly transmitted in eggs. In the United Kingdom, a widespread vaccination

program was implemented for egg-laying hens to reduce transmission of �� Enteritidis. The

programme was successful in achieving a significant decrease of human infections caused solely

by �� Enteritidis (Gast � ��., 2007).

FUTURE PREDICTIONS AND PERSPECTIVES Zoonotic infections are responsible for a large and growing proportion of the mortality and

morbidity throughout the world. Foodborne zoonoses will likely continue to be important in the

future as the global population moves more toward meat products as a source of protein

(Merianos � ��., 2007; Murphy � ��., 2008). In general, the human infections caused by NTS

will most likely not significantly decrease in the future unless the global intervention towards

eggs succeeds. However, the serovar distribution will probably on a global scale be influenced by

increased trade, travel and consumption of exotic food or food produced to low costs (III; IV;

V;VI ).

Most of the research conducted in the last decades has been focused on �� Enteritidis and ��

Typhimurium, while relatively little is know about the epidemiology of rare serovars with the

potential to increase globally.

Recently focus on NTS in the African region revealed that serovars causing gastrointestinal

infections also are invasive (Morpeth � ��., 2009). We predict to see stronger evidence of NTS

causing bacteremia in humans from Africa in time due to the efforts by WHO to implement and

enhance �� surveillance and burden of illness studies in this area. Another alarming

development which lay ahead is the increasing frequency of antimicrobial resistance in NTS. In

the last decade, the Western world has tried to minimise the usage of fluoroquinolones and third

and fourth generation cephalosporins in both the human and veterinary medicine. These two drug

classes are paramount in treating salmonellosis caused my multi-drug resistant strains. Recently,

39

the WHO has stated that antimicrobial resistance is a global public health concern and has top

priority. Evidence shows extensive usage and resistance to fluoroquinolones and third and fourth

generation cephalosporins from developing countries, driven in part by low prices and weak or

absent use restrictions (Archambault � ��., 2006; Aarestrup � ��., 2007; Fabre � ��., 2009; Lee � �

�., 2009; II; IV).

In the past two decades, our understanding of �� biology and epidemiology has grown

tremendously. Advances in technology are moving toward rapid, high-throughput,

comprehensive analytical methods. It is highly likely that many, if not all, phenotyping

techniques will be supplanted by platforms based on DNA sequence and gene expression tools.

To make this transition, it will be necessary to validate the sequenced-based methods to the older

phenotypic methods in order to avoid the loss of knowledge and the ability to compare with

“historical” data (Hyytiä-Trees � ��., 2007). It is expected that within the next decade, microbial

genomic sequencing will become inexpensive and routine worldwide. Currently, the technique is

faced with a limiting factor of how to assemble, process and handle the large amount of data full

genome sequencing will create. Despite of this limitation, software to resolve this problem will

most likely be developed in the future making rapid tools for analysis available for extraction of

biological and epidemiological data. The data could be applied in multiple ways for typing,

genetic comparison or even non-specific vaccines.

Over the past decade, the WHO GFN has promoted capacity building for integrated, laboratory-

based surveillance through training courses and activities around the world. The network consists

of more than 1200 researchers in more than 700 institutes in 158 member states and 64 training

courses have been conducted to date. It is expected that more countries will establish ��

laboratory-based or integrated laboratory-based surveillance. One challenge is to ensure

international harmonization of surveillance systems so that data can be directly compared.

Despite of the good intention for conducting surveillance in a global context the benefit for

developing countries might be controversial. �� infections in developing countries are

frequently endemic resulting in a high incidence of symptomatic infections primarily in children

causing immunity. Food consumption is often based on locally produced food and with the

acquired immunity it is likely to result in much fewer outbreaks compared to e.g. the United

States. It will require huge investments in sanitation infrastructure as a whole to decrease the

40

burden of �� in these countries in contrast to a recall of a specific food product in a

developed country (Zaidi � ��., 2009).

The recent development of source attribution models and the increased number of developed

countries conducting integrated laboratory-based surveillance will most certainly results in more

countries attributing human infections to various sources. An increased number of countries

performing source attribution will probably enable epidemiologists to target control and

prevention programmes to the principal reservoirs and serovars responsible for the majority of

salmonellosis cases in a global context to avoid a new pandemic. In addition, applied research

linking across the human, livestock and food products is needed to increase preparedness

planning and the development of evidence-based approaches to zoonotic disease prevention and

control (Merianos � ��., 2007). Therefore, long term planning that takes into consideration the

unique nature of zoonosis is needed.

CONCLUSIONS AND RECOMMENDATIONS The studies included in this thesis have confirmed the importance of international travel and

consumption of imported food for NTS infections in humans. Globally, the serovars �. Enteritidis

and �. Typhimurium seems to decrease in relative importance whereas a large diversity of other

non-specific serovars are increasing; indicating that serovar specific interventions for �.

Enteritidis and �. Typhimurium are ineffective against other NTS. Reliable serotyping data

revealed large differences among commonly isolated serovars between continents and less

difference between countries within the same continent. Global surveillance identified common

problems in several countries, which then was elucidated by detailed epidemiological and

molecular studies. Country specific studies have also revealed differences between regions within

a country associated with specific risk factors. The thesis illustrates the value of global

harmonised surveillance in detecting global trends and identifying local and global problems

which then were elucidated. The thesis also illustrates the great value of combining epidemiology

and molecular microbiology. There is still a huge lack of knowledge regarding the global

epidemiology of ��. There is a global need for implementing timely systematic

integrated laboratory-based surveillance for �� in combination with extensive collection

of epidemiological data to target prevention and intervention strategies to diminish the worldwide

burden of human salmonellosis.

41

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59

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Article I

WHO Global Salm-Surv External Quality Assurance System (EQAS) for serotyping of

Salmonella isolates, 2000 - 2007.

Rene S. Hendriksen,1* Matthew Mikoleit,2 Valeria P. Carlson,2 Susanne Karlsmose,1 Antonio

R. Vieira,1 Arne B. Jensen,1 Anne Mette Seyfarth,1 Stephanie M. Delong,2 François-Xavier

Weill,3 Danilo Marino Armando Lo Fo Wong,4 Frederick J. Angulo,2 Henrik C. Wegener,1

Frank M. Aarestrup1

1 National Food Institute, WHO Collaborating Centre for Antimicrobial Resistance in

Foodborne Pathogens and Community Reference Laboratory for Antimicrobial Resistance,

Technical University of Denmark, Copenhagen, Denmark 2 Centers for Disease Control and Prevention, WHO Collaborating Centre for Surveillance,

Epidemiology and Control of �� and other Foodborne Diseases, the Enteric Disease

Epidemiology Branch, Atlanta, GA, USA 3 Institut Pasteur, WHO Collaborating Centre for ��, Paris, France 4 World Health Organization, Department of Food Safety, Zoonoses and Foodborne Diseases,

Geneva, Switzerland

Corresponding author: Rene S. Hendriksen,

National Food Institute,

Bülowsvej 27, DK-1790 Copenhagen V, Denmark

Phone: +45 35 88 70 00

Fax: +45 35 88 60 01

E-mail: [email protected]

Foodborne Pathog Dis. 2008 Oct; 5 (5): 605-19.

JOURNAL OF CLINICAL MICROBIOLOGY, Sept. 2009, p. 2729–2736 Vol. 47, No. 90095-1137/09/$08.00�0 doi:10.1128/JCM.02437-08Copyright © 2009, American Society for Microbiology. All Rights Reserved.

WHO Global Salm-Surv External Quality Assurance System forSerotyping of Salmonella Isolates from 2000 to 2007�

Rene S. Hendriksen,1* Matthew Mikoleit,2 Valeria P. Carlson,2 Susanne Karlsmose,1 Antonio R. Vieira,1Arne B. Jensen,1 Anne Mette Seyfarth,1 Stephanie M. DeLong,2 Francois-Xavier Weill,3

Danilo Marino Armando Lo Fo Wong,4 Frederick J. Angulo,2Henrik C. Wegener,1 and Frank M. Aarestrup1

National Food Institute, WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens, andCommunity Reference Laboratory for Antimicrobial Resistance, Technical University of Denmark, Copenhagen, Denmark1;

Centers for Disease Control and Prevention, WHO Collaborating Centre for Surveillance, Epidemiology and Control ofSalmonella and other Foodborne Diseases, Enteric Disease Epidemiology Branch, Atlanta, Georgia2; Institut Pasteur,

WHO Collaborating Centre for Salmonella, Paris, France3; and World Health Organization, Department ofFood Safety, Zoonoses and Foodborne Diseases, Geneva, Switzerland4

Received 19 December 2008/Returned for modification 1 April 2009/Accepted 16 June 2009

An international external quality assurance system (EQAS) for the serotyping of Salmonella species wasinitiated in 2000 by WHO Global Salm-Surv to enhance the capacity of national reference laboratories toobtain reliable data for surveillance purposes worldwide. Seven EQAS iterations were conducted between 2000and 2007. In each iteration, participating laboratories submitted serotyping results for eight Salmonellaisolates. A total of 249 laboratories in 96 countries participated in at least one EQAS iteration. A total of 756reports were received from the participating laboratories during the seven EQAS iterations. Cumulatively, 76%of participating laboratories submitted data for all eight strains, and 82% of strains were correctly serotyped.In each iteration, 84% to 96% of the laboratories correctly serotyped the Salmonella enterica serovar Enteritidisisolate that was included as an internal quality control strain. Regional differences in performance wereobserved, with laboratories in Central Asia and the Middle East performing less well overall than those inother regions. Errors that resulted in incorrect serovar identification were typically caused by difficulties in thedetection of the phase two flagellar antigen or in differentiation within antigen complexes; some of these errorsare likely related to the quality of the antisera available. The results from the WHO Global Salm-Surv EQAS,the largest of its kind in the world, show that most laboratories worldwide are capable of correctly serotypingSalmonella species. However, this study also indicates a continuing need for improvement. Future trainingefforts should be aimed at enhancing the ability to detect the phase two flagellar antigen and at disseminatinginformation on where to purchase high-quality antisera.

Salmonella species are among the most important food-borne pathogens, leading to millions of cases of diarrheal ill-ness and thousands of hospitalizations and deaths worldwideeach year (3, 7).

More than 2,500 serovars of Salmonella enterica have beenidentified; most human infections are caused by a limited num-ber of serovars. In many developed countries, Salmonella en-terica serovars Typhimurium and Enteritidis are the most com-mon causes of human salmonellosis (5, 6, 8).

In other regions, however, other serovars have been re-ported to be more prevalent (1, 3, 5). Changes in the preva-lences of specific serovars can result from the movements ofpeople, animals, and food. Correct serotyping is essential fordiscerning such changes and therefore is essential for efficientoutbreak detection and response resulting from laboratory-based surveillance.

In January 2000, the World Health Organization (WHO)launched WHO Global Salm-Surv, a global effort to enhancethe laboratory-based surveillance of Salmonella infections and

other food-borne diseases and to promote prevention and con-trol activities. Enhancing worldwide serotyping of Salmonellaspecies is a key objective of WHO Global Salm-Surv and isfacilitated by bench training at international training courses.

To ascertain the performance of participating laboratoriesand thereby promote enhanced laboratory-based surveillance,an external quality assurance system (EQAS) was establishedas a part of the WHO Global Salm-Surv program in 2000.Since then, the WHO Global Salm-Surv EQAS has grown tobe the largest of its kind worldwide (4, 9). Among other activ-ities, the EQAS conducts an assessment of the capacities oflaboratories to correctly serotype Salmonella species by ship-ping eight blinded Salmonella isolates for serotyping. Iterationsof the EQAS are organized yearly by Denmark’s NationalFood Institute (DTU Food) in collaboration with WHO, theU.S. Centers for Disease Control and Prevention (CDC), andFrance’s Institut Pasteur. The WHO Global Salm-Surv EQASis a self-evaluating system: after submitting their results to theEQAS Web-based reporting system via a secured individuallog-in pass code, participants receive a report that itemizeserrors relative to the expected results. The report is intendedto be used by the participants for evaluating the accuracy ofcurrent techniques and the quality of antisera. The goal is tohave all laboratories perform serotyping of Salmonella with a

* Corresponding author. Mailing address: National Food Institute,Bulowsvej 27, DK-1790 Copenhagen V, Denmark. Phone: 45 35 88 7000. Fax: 45 35 88 60 01. E-mail: [email protected].

� Published ahead of print on 1 July 2009.

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maximum of one error out of eight isolates. Here we report theresults of the first seven iterations of the WHO Global Salm-Surv EQAS Salmonella serotyping procedures, conductedfrom 2000 to 2007. In 2005, no iteration was conducted, due toan internal assessment of the system.

MATERIALS AND METHODS

Participation in the WHO Global Salm-Surv EQAS is open to all laboratoriesfree of charge. An invitation to participate in each EQAS iteration was an-nounced through Electronic Discussion Group messages, which are received byWHO Global Salm-Surv members. All members receive these messages bye-mail or by fax. Previous messages are archived on the WHO Global Salm-Survwebsite (http://www.who.int/salmsurv/activities/bulletin_board/en/). In 2007,WHO Global Salm-Surv membership included �1,000 microbiologists and epi-demiologists from 152 countries representing �140 national reference laborato-ries (animal, food, or public health). Scientists who attended WHO GlobalSalm-Surv international training courses were automatically registered as WHOGlobal Salm-Surv members. Through 2008, 56 training courses were held at 17training sites worldwide. The training curricula provided in these courses typi-cally include both classroom and laboratory instructional modules on the iden-tification and serotyping of Salmonella species.

Eight Salmonella strains, based on the global prevalence of the serotypes, wereselected for each EQAS iteration (3). Strains were obtained from the isolatecollection of DTU Food. The same strain of Salmonella serovar Enteritidis wasincluded as an internal quality control in 2000, 2001, 2004, 2006, and 2007. Forthe 2002 iteration, an alternate but phenotypically identical strain of Salmonellaserovar Enteritidis was chosen. All other strains were included only once in theEQAS iterations. Some serovars (e.g., Salmonella serovar Typhimurium) wereutilized in multiple iterations; however, these strains had different antimicrobialresistance profiles (Table 1).

All Salmonella isolates included in the EQAS were serotyped at DTU Food,the CDC, and Institut Pasteur; the serotypes obtained served as the referencestandard. O (somatic) and H (flagellar) antigens were characterized by aggluti-nation with hyperimmune sera, and serotypes were assigned according to theKauffmann-White scheme (11).

Testing instructions and a “participating laboratory record sheet” (PLRS)were copied to a compact disc, enclosed with the Salmonella agar stab cultures indouble-pack containers (class UN 6.2), and sent to the participating laboratoriesaccording to the International Air Transport Association regulations as “Biolog-ical Substance Category B,” classified as UN 3373. Prior to shipping, eachparticipating laboratory was notified of the shipping arrangements that had beenmade for the parcels and was given the airway bill number to enable it to trackthe package and pick it up from the airport. Import permits were necessary forshipping the parcels to several countries.

WHO Global Salm-Surv EQAS participation was free of charge, but eachparticipating laboratory was expected to cover the expenses associated with itstesting of the strains in its facility. Participating laboratories were provided withinstructions for the initial subculture of the Salmonella strains. Participatinglaboratories serotyped the isolates using protocols routinely utilized in theirinstitutions; therefore, instructions for serotyping the isolates were not provided.Laboratories were required to submit results by uploading the PLRS onto theWHO Global Salm-Surv website or by submitting the completed PLRS by fax toDTU Food.

After submitting results, each participating laboratory received an individualreport. Laboratories that submitted results via the website received an instantreport via the secure website, and laboratories that sent the results by fax ore-mail received the report using media. The individual reports included all errorsand suggestions on how to either solve or investigate the problem. Errors aredefined as results that are different from the expected serotypes. Errors werereported as incorrect results only, and no attempt was made to quantify theirseverity. Fisher exact tests were performed to assess the significance of theobserved changes in correct serotyping results and reported errors. Laboratoryparticipation over the years was assessed by logistic regression, and a P valueof �0.05 was regarded as significant for all statistical tests. SAS Enterprise Guidesoftware (version 3.0; SAS Institute, Cary, NC) was used for the statisticalanalyses.

RESULTS

A total of 249 laboratories in 97 countries participated in atleast one of the seven iterations of EQAS from 2000 to 2007;44 laboratories in 35 countries participated in 2000, 96 labo-ratories in 55 countries in 2001, 99 laboratories in 61 countriesin 2002, 127 laboratories in 72 countries in 2003, 127 labora-tories in 71 countries in 2004, 130 laboratories in 66 countriesin 2006, and 140 laboratories in 68 countries in 2007. Theaverage number of participating laboratories per EQAS itera-tion between 2000 and 2007 was 102. One hundred twenty-fivelaboratories participated in three or more iterations, and 92laboratories participated in four or more iterations. The par-ticipating laboratories included national reference laborato-ries; veterinary, food, and regional public health laboratories;and clinical laboratories. One or more institutions from thecountries listed in Table 2 participated in at least one of theEQAS iterations.

The percentage of participating laboratories that performedserotyping on all eight strains during the seven iterationsranged from 54% to 92%, with an average of 76% (Table 3).The percentage of participating laboratories that correctly se-rotyped the Salmonella serovar Enteritidis isolate that wasincluded in six of the seven iterations increased over the years,although the increase was not statistically significant (P �0.37), from 92% (2000) to 96% (2007).

The percentage of correct serotyping results oscillated in theinitial years, decreasing from 76% in 2000 to 72% in 2001 andrising to 91% in 2002. In the 2003 cycle, the percentage ofcorrect serotyping results was 80%, and since then it has in-creased annually, reaching 88% in 2007. Overall, logistic re-gression indicates a significant increase in the percentage ofcorrect serotyping results over the years (P � 0.01), and theaverage percentage of correctly serotyped isolates across all 7years was 82% (Table 3).

The goal of the EQAS program is for all participating lab-oratories to perform Salmonella serotyping with a maximum ofone error. A total of 756 PLRSs were received during the sevenEQAS iterations. The percentage of laboratories reaching thethreshold of reporting one or zero errors increased signifi-cantly (P � 0.04), from 48% in 2000 to 68% in 2007 (data notshown). In addition, the 2007 iteration was the first in whichevery participating laboratory correctly identified at least onestrain.

A wide range of incorrect results was observed across theseven-cycle study period. The rate of errors ranged from 3.6%(2007) to 41.0% (2006). The rate of errors also differed widelybetween the different isolates within a single year. For exam-ple, in 2001, rates of incorrect results for a single isolate rangedfrom 9.6% for the Salmonella serovar Typhimurium isolate to38.0% for a Salmonella serovar Kottbus isolate.

A Salmonella enterica subsp. enterica serovar 4,5,12:i:� iso-late included in the 2006 iteration accounted for the greatestnumber of incorrect results (Table 1). A total of 38 laborato-ries (31.1%) incorrectly serotyped this isolate as Salmonellaserovar Typhimurium. Salmonella enterica subsp. enterica ser-ovar 4,5,12:i:� is a common monophasic variant in both Eu-rope and North America. Characterization of other Salmonellaenterica subsp. enterica serovar 4,5,12:i:� strains suggests thatthese strains are most likely variants of Salmonella serovar

2730 HENDRIKSEN ET AL. J. CLIN. MICROBIOL.


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TABLE 1. List of Salmonella serotypes and errors (EQAS, 2000 to 2007)

Yr WHOno. Correct serotype Correct formula No. of labs

serotyping%

Errors Deviating serotype (formula) (no. of labs)a

2007 7.1 Concord 6,7:l,v:1,2 125 19.2 Mkamba (I 6,7:l,v:1,6) (5), Potsdam (I 6,7,14:l,v:e,n,z15) (4), Colorado(I 6,7:l,w:1,5), Bonn (I 6,7:l,v:e,n,x), Gabon (I 6,7:l,w:1,2), Kortrijk(I 6,7:l,v:1,7), Langeveld (I 6,7:l,w:e,n, z15), Nessziona (I 6,7:l,z13:1,5),Ohio (I 6,7,14:b:l,w), Oakland (I 6,7:z:1,6,�7�), Panama (I 1,9,12:l,v:1,5),Richmond (I 6,7:y:1,2), Strathcona (I 6,7:l,z13, z28:1,7), Thompson(I 6,7,14:k:1,5), Virchow (I 6,7,14:r:1,2), Wil (I 6,7:d: l,z13, z28),Salmonella spp.

2007 7.2 Enteritidis 9,12:g,m:� 140 3.6 Blegdam (I 9,12:g,m,q:�), Dublin (I 1,9,12;�Vi�:g,p:�), Potsdam(I 6,7,14:l,v:e,n,z15), Rissen (I 6,7,14:f,g:�), Warragul (I �1�,6,14,�25�:g,m:�)

2007 7.3 Livingstone 6,7,d:l,w 128 10.9 Kambole (I 6,7:d:1;�2�,7) (3), Gabon (I 6,7:l,w:1,2) (2), Paratyphi C(I 6,7,�Vi�:c:1,5) (2), Gombe (I 6,7,14:d:e,n,z15), Herston (I 6,8:d:e,n,z15), Isangi (I 6,7,14:d:1,5), Kisii (I 6,7:d:1,2), Nievkerk (I 6,7,14:d:z6),Ohio (I 6,7,14:b:l,w), Typhi (I 9,12,�Vi�:d:�)

2007 7.4 Montevideo 6,7:g,m,s:� 131 6.9 Salmonella enterica subsp. II (3), Chincol (I 6,8:g,m,�s�:�e,n,x�), Eboko(I 6,8:b:1,7), Menston (I 6,7:g,s,�t�:�1,6�), Othmarschen(I 6,7,14:g,m,�t�:�), Rissen (I 6,7,14:f,g:�)

2007 7.5 Mbandaka var. 14� 6,7,14:z10:e,n,z15 131 14.5 Braenderup (I 6,7,14:e,h:e,n,z15) (6), Djugu (I 6,7:z10:e,n,x) (2), Aequatoria(I 6,7:z4,z23:e,n,z15), Denver (I 6,7:a:e,n,z15), Georgia (I 6,7:b:e,n,z15),Glostrup (I 6,8:z10:e,n,z15), Gombe (I 6,7,14:d:e,n,z15), Kaduna(I 6,7,14:c:e,n,z15), Kastrup (I 6,7:e,n,z15:1,6), Larose (I 6,7:g,z51:e,n,z15),Lockleaze (I 6,7,14:b:e,n,x), Montevideo (I 6,7,14:g,m,�p�,s:�1,2,7�),Papuana (I 6,7:r:e,n,z15)

2007 7.6 Elisabethville 3,10:r:1,7 130 10.0 Weltevreden (I 3,10,�15�:r:z6) (5), Simi (I 3,10:r:e,n,z15) (2), Salmonellaspp. (2),Give (I 3,10,�15�, �15,34�:�d�,l,v:1,7), Montevideo(I 6,7,14:g,m,�p�,s:�1,2,7�), Seegefeld (I 3,10:r,i:1,2), Westhampton(I 3,10,�15�, �15,34�:g,s,t:�)

2007 7.7 Poona 13,22:z:1,6 121 14.0 Bristol (I 13,22:z:1,7) (2), Farmsen (I 13,23:z:1,6) (2), Salmonella spp. (2),Borbeck (I 13,22:l,v:1,6), Derby (I 1,4,�5�,12:f,g:�1,2�), Durban(I 9,12:a:e,n,z15), Gabon (I 6,7:l,w:1,2), Kuru (I 6,8:z:l,w), Manhattan(I 6,8:d:1,5), Marburg (I 13,23:k:�), Montevideo (I 6,7,14:g,m,�p�,s:�1,2,7�),Nyanza (I 11:z:z6:�z83�), Saugus (I 40:b:1,7), Salmonella subsp. II

2007 7.8 Isangi 6,7:d:1,5 136 13.2 Kisii (I 6,7:d:1,2) (4), Kambole (I 6,7:d:1;�2�,7) (2), Livingstone(I 6,7,14:d:l,w) (2), Paratyphi C (I 6,7,�Vi�:c:1,5) (2), Wil(I 6,7:d:l,z13,z28) (2), Choleraesuis (I 6,7:c:1,5), Herston (I 6,8:d:e,n,z15),Manhattan (I 6,8:d:1,5), Nievkerk (I 6,7,14:d:z6), Poitiers (I 6,7:z:1,5),Salmonella spp.

2006 6.1 Salmonella I4,5,12:i:�

1,4,12:i:� 122 41.0 Typhimurium (I 1,4,�5�,12:i:1,2) (38), Farsta (I 4,5:i:e,n,x) (3), Gloucester(I 1,4,12,27:i:l,w) (2), Agama (I 4,12:i:1,6), Lagos (I 1,4,�5�,12:i:1,5),Mathura (I 9,46:i:e,n,z15), Paratyphi B (I 1,4,�5�,12:b:1,2), Tsevie(I 4,12:i:e,n,z15), Tumodi (I 1,4,12,27:l,�z15�,z28:1,5), Salmonella subsp. V

2006 6.2 Saintpaul 1,4,12:e,h:1,2 119 11.8 Sandiego (I 4;�5�,12:e,h:e,n,z15) (6), Chester (I 1,4,�5�,12:e,h:e,n,x) (2),Reading (I 1,4,�5�,12:e,h:1,5), Bardo (I 8,e,h:1,2), Typhimurium(I 1,4,�5�,12:i:1,2), Paratyphi B (I 1,4,�5�,12:b:1,2), Chartres(I 1,4,12:e,h:l,w), I 4,12:�:�b

2006 6.3 Virchow 6,7:r:1,2 121 9.9 Nigeria (I 6,7:r:1,6) (4), I 6,7:r:� (3), Bsilla (I 6,8:r:1,2), Infantis(I 6,7,14:r:1,5), Lomita (I 6,7:e,h:1,5), Papuana (I 6,7:r:e,n,z15), Ngili(I 6,7:z10:1,7)

2006 6.4 Rissen 6,7:f,g:� 118 11.0 Montevideo (I 6,7,14:g,m,�p�,s:�1,2,7�) (5), Eingedi (I 6,7:f,g,t:1,2,7) (2),Othmarschen (I 6,7,14:g,m,�t�:�) (2), Blegdam (I 9,12:g,m,q:�), Derby(I 1,4,�5�,12:f,g:�1,2�), Oranienburg (I 6,7,14:m,t:�z57�), Sandow(I 6,8:f,g:e,n,z15)

2006 6.5 Reading 4,5,12:e,h:1,5 121 16.5 Saintpaul (I 1,4,�5�,12:e,h:1,2) (6), Sandiego (I 4;�5�,12:e,h:e,n,z15) (3),Chester (I 1,4,�5�,12:e,h:e,n,x) (2), Bradford (I 4,12,27:r:1,5), Derby(I 1,4,�5�,12:f,g:�1,2�), Enteritidis (I 1,9,12:�f�,g,m,�p�:�1,7�), Eppendorf(I 1,4,12,27:d:1,5), Hato (I 1,4,�5�,12:g,m,s:�), Mono (I 4,12:l,w:1,5),Paratyphi B (I 1,4,�5�,12:b:1,2), Typhimurium (I 1,4,�5�,12:i:1,2),I 4,5,12:�:�b

2006 6.6 Enteritidis 9,12:g,m:� 124 6.5 Gallinarum (I 1,9,12:�,�) (2), Berta (I 1,9,12:�f�,g,�t�:�), Blegdam(I 9,12:g,m,q:�), Bournemount (I 9,12:e,h:1,2), London (I 3,10,�15�:l,v:1,6),Montevideo (I 6,7,14:g,m,�p�,s:�1,2,7�), Typhi (I 9,12,�Vi�:d:�)

2006 6.7 London 3,10:l,v:1,6 111 9.9 Amherstiana (I 8:l,v:1,6) (2), Give (I 3,10,�15��15,34�:�d�,l,v:1,7) (2),Birmingham (I 3,10:d:l,w), Clackamas (I 4,12:l,v:1,6), Nchanga(I 3,10,�15�,l,v:1,2), Ruzizi (I 3,10:l,v:e,n,z15), Sinstorf (I 3,10:l,v:1,5),Stockholm (I 3,10,�15�:y:z6), Suberu (I 3,10:g,m:�)

2006 6.8 Give 3,10:l,v:1,7 114 9.6 London (I 3,10,�15�:l,v:1,6) (4), Nchanga (I 3,10,�15�,l,v:1,2) (2),Amsterdam (I 3,10,�15��15,34�:g,m,s:�), Bredeney (I 1,4,12,27:l,v:1,7),Kortrijk (I 6,7:l,v:1,7), Mokola (I 3,10:y:1,7), Stormont (I 3,10:d:1,2)

2004 5.1 Give 3,10:l,v:1,7 111 26.1 London (I 3,10,�15�:l,v:1,6) (9), Parkroyal (I 1,3,19:l,v:1,7) (3), Meleagridis(I 3,10,�15��15,34�:e,h:l,w) (3), Joal (I 3,10:l,z28:1,7) (2), Nchanga(I 3,10,�15�,l,v:1,2) (2), Anatum (I 3,10,�15��15,34�:e,h:1,6),Assinie (I 3,10:l,w:z6), Cannonhill (I 3,10,�15�,19:y:e,n,x), Elisabethville(I 3,10:r:1,7), Litchfield (I 6,8:l,v:1,2), Newbrunswick,b Nyborg(I 3,10,�15�:e,h:1,7) Ruzizi (I 3,10:l,v:e,n,z15), Sinchew (I 3,10:l,v:z35),Sinstorf (I 3,10:l,v:1,5)

2004 5.2 Braenderup var. 14� 6,7,14:eh:enz15 110 6.8 Larochelle (I 6,7:e,h:1,2) (2), Norwich (I 6,7:e,h:1,6) (2), Larose(I 6,7:g,z51:e,n,z15), Lomita (I 6,7:e,h:1,5), Sanjuan (I 6,7:a:1,5)

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TABLE 1—Continued


serotyping%


2004 5.3 Corvallis 8,20:z4z23:� 88 20.5 Chailey (I 6,8:z4,z23:�e,n,z15�) (5), Dabou (I 8,20,z4,z23:l,w) (4), Albany(I 8,20,z4,z23:�) (3), Ackwepe (I 9,46:l,w:�), Breda (I 6,8:z4,z23:e,n,x),Hindmarsh (I 8,20:r:1,5), Kallo (I 6,8:k:1,2), Kentucky (I 8,20:i:z6), Noya(I 8:r:1,7)

2004 5.4 Heidelberg 4,12:r:1,2 116 16.3 Magumeri (I 1,6,14,25:e,h:1,6) (2), Remo (I 1,4,12,27:r:1,7) (2), Typhimurium(I 1,4,�5�,12:i:1,2) (2), Winneba (I 4,12:r:1,6) (2), Africana (I 4,12:r,i:l,w),Agona (I 1,4,�5�,12:f,g,s:�1,2�), Fayed (I 6,8:l,w:1,2), Hidalgo(I 6,8:r,�i�:e,n,z15), Kalamu (I 1,5,�5�12:z4,z24:�1,5�), Kiel (I 1,2,12:g,p:�),Ljubljana (I 4,12,27:k:e,n,x), Paratyphi B (I 1,4,�5�,12:b:1,2), Saintpaul(I 1,4,�5�,12:e,h:1,2), Sandiego (I 4;�5�,12:e,h:e,n,z15), Schwarzengrund(I 1,4,12,27:d:1,7)

2004 5.5 Chester 4,5,12:eh:enx 110 40.0 Sandiego (I 4;�5�,12:e,h:e,n,z15) (26), Saintpaul (I 1,4,�5�,12:e,h:1,2) (5),Abortusequi (I 4,12:�:e,n,x) (3), Agona (I 1,4;�5�,12:f,g,s:�1,2�), Goldcoast(I 6,8:r:l,w), Haıfa (I 1,4,�5�,12:z10:1,2), Kaapstad (I 4,12:e,h:1,7), Magumeri(I 1,6,14,25:e,h:1,6), Paratyphi B (I 1,4,�5�,12:b:1,2), Sarajane(I 1,4,�5�,12,27:d:e,n,x) Texas (I 4,�5�,12:k:e,n,z15)

2004 5.6 Corvallis 8,20:z4z23:� 87 23.0 Albany (I 8,20,z4,z23:�) (5), Dabou (I 8,20,z4,z23:l,w) (4), Hailey(I 6,8:z4,z23:�e,n,z15�) (3), Bellevue (I 8:z4,z23:1,7) (2), Rechovot(I 8,20:e,h:z6) (2), Newport (I 6,8,20:e,h:1,2:�z67�) (2), Bardo (I 8:e,h:1,2),Bovismorbificans (I 6,8,20:r,�i�:1,5)

2004 5.7 Mbandaka 6,7,:z10:enz15 104 20.2 Djugu (I 6,7:z10:e,n,x) (7), Menden (I 6,7:z10:1,2) (4), Redba (I 6,7:z10:z6)(2), Gabon (I 6,7:l,w:1,2), Infantis (I 6,7,14:r:1,5), Lindenburg(I 6,8:i:1,2), Lockleaze (I 6,7,14:b:e,n,x), Namibia (I 6,7:c:e,n,x), Omuna(I 6,7:z10:z35), Paratyphi C (I 6,7,�Vi�:c:1,5), Thompson (I 6,7,14:k:1,5)

2004 5.8 Enteritidis 9,12:gm:� 120 5.8 Blegdam (I 9,12:g,m,q:�) (3), Berta (I 1,9,12:�f�,g,�t�:�), Gallinarum(I 1,9,12:�,�), Goverdhan (I 9,12:k:1,6), Typhi (I 9,12,�Vi�:d:�)

2003 4.1 Montevideo 6,7:g,m,s:� 119 10.9 Salmonella subsp. II (4), Menston (I 6,7:g,s,�t�:�1,6�) (3), Oakland(I 6,7:z:1,6,�7�), Oranienburg (I 6,7,14:m,t:�z57�), Riggil (I 6,7:g,�t�:�),Rissen (I 6,7,14:f,g:�), Sanjuan (I 6,7:a:1,5), Schwarzengrund(I 1,4,12,27:d:1,7)

2003 4.2 Schwarzengrund 4,12:d:1,7 119 15.1 Stanley (I 1,4,�5�,12,27:d:1,2) (5), Ayinde (I 1,4,12,27:d:z6) (2), Ahmadi(I 1,3,19:d:1,5), Brezany (I 1,4,12,27:d:1,6), Duisburg (I 1,4,12,27:d:e,n,z15),Eppendorf (I 1,4,12,27:d:1,5), Kambala (I 1,42:c:z6), Magumeri(I 1,6,14,25:e,h:1,6), Mons (I 1,4,12,27:d:l,w), Montevideo(I 6,7,14:g,m,�p�,s:�1,2,7�), Sarajane (I 1,4,�5�,12,27:d:e,n,x), Southampton(I 4,12,27:r:z6), Typhimurium (I 1,4,�5�,12:i:1,2)

2003 4.3 Paratyphi B (var.Java)

1,4,5,12:b:1,2 118 23.7 Abony (I 1,4,�5�,12,27:b:e,n,x) (3), Typhimurium (I 1,4,�5�,12:i:1,2) (3),Derby (I 1,4,�5�,12:f,g:�1,2�) (2), Schleissheim (I 4,12,27:b:�) (2),Saintpaul (I 1,4,�5�,12:e,h:1,2) (2), Salmonella subsp. (2), Uppsala(I 1,4,12,27:b:1,7) (2), Athinai (I 6,7:i:e,n,z15), Agona(I 1,4,�5�,12:f,g,s:�1,2�), Brandenburg (I 4,�5�,12:l,v:e,n,z15), Fortune(I 1,4,12,27:z10:z6), Hato (I 1,4,�5�,12:g,m,s:�), Indiana (I 1,4,12:z:1,7),Lagos (I 1,4,�5�,12:i:1,5), Onarimon (I 1,9,12:b:1,2) Sandiego(I 4;�5�,12:e,h:e,n,z15), Wagenia (I 1,4,12,27:b:e,n,z15), II Chartres(I 4,12: e,n,x:1,2,7), Abony (I 1,4,12,27:b:�e,n,x�), Salmonella subsp. II

2003 4.4 Panama 9,12:l,v:1,5 120 14.2 Enteritidis (I 1,9,12:�f�,g,m,�p�:�1,7�) (2), Javiana (I 1,9,12:l,z26:1,5) (2),Kapemba (I 9,12:l,v:1,7) (2), Lawndale (1,9,12:z:1,5) (2), Dublin(I 1,9,12,�Vi�:g,p:�), Goettingen (9,12:l,v:e,n,z15), London(I 3,10,�15�:l,v:1,6), Irumu (I 6,7:l,v:1,5), Italiana,b Itami (I 9,12:l,z13:1,5),Paratyphi C (I 6,7,�Vi�:c:1,5), Sarajane (I 1,4,�5�,12,27:d:e,n,x), Victoria(I 1,9,12:l,w:1,5)

2003 4.5 Cerro 18:z4,z23:� 91 35.2 Aarhus (I 18:z4,z23:z64) (9), Bousso (I 1,6,14,25:z4,z23:e,n,z15) (5),Salmonella subsp. III (3), Salmonella subsp. IV (3), Arapahoe(I 6,14:z4,z23:1,5), Blukwa (I 6,14,18:z4,z24:�), Chailey(I 6,8:z4,z23:�e,n,z15�), Chichiri (I 6,14,24:z4,z24:�), Corvallis(I 8,20:z4,z23:�z4�), Memphis (I 18:k:1,5), Obogu (I 6,7:z4,z23:1,5)Siegburg,b Tallahassee (I 6,8:z4,z32:�), Usumbura (I 6,14,18:d:1,7),Virchow (I 6,7,14:r:1,2), I 6,7:z4,z23:�, Salmonella subsp. II

2003 4.6 Havana 13,23:f,g:� 96 19.8 Raus (I 13,22:f,g:e,n,x) (6), Okatie (I 13,23:g,�s�,t:�) (2), Afula(I 6,7:f,g,t:e,n,x), Agbeni (I 1,13,23:g,m,�s�,�t�:�) Berta (I 1,9,12:�f�,g,�t�:�),Bron (I 13,23:g,m:�e,n,z15�) Chagoua (I 1,13,23:a:1,5), NewYork(I 13,22:g,s,t:�), Poona (I 1,13,22:z:1,6:�z44�), Rissen (I 6,7,14:f,g:�), Tees(I 16:f,g:�), Tschangu (I 1,13,23:e,h:1,5), Worthington (I 1,13,23:z:l,w)

2003 4.7 Vinohrady 28:m,t:� 75 29.3 Abadina (I 28:g,m:�e,n,z15�) (4), Morillons (I 28:m,t:1,6) (4), Salmonellasubsp. II (3), Croft (I 28:g,m,s:�e,n,z15�) (2), Hatfield (I 28:d:1,6), Nitra(I 2,12:g,m:�), Othmarschen (I 6,7,14:g,m,�t�:�), Panama(I 1,9,12:l,v:1,5), Pomona (I 28:y:1,7:�z60�), Southbank(I 3,10,�15�,�15,34�:m,t:�1,6�) Techimani (I 28:c:z6), Tennessee(I 6,7,14:z29:�1,2,7�), II 28.9,�m�,�s�,t:1,5

2003 4.8 Singapore 6,7:k:enx 113 15.0 Thompson (I 6,7,14:k:1,5) (5), Escanaba (I 6,7:k:e,n,z15) (2), Salmonellasubsp. II (3), Braenderup (I 6,7,14:e,h:e,n,z15). Kastrup (I 6,7:e,n,z15:1,6)Ljubljana (I 4,12,27:k:e,n,x), Mbandaka (I 6,7,14:z10:e,n,z15), Norwich(I 6,7:e,h:1,6), Paratyphi C (I 6,7,�Vi�:c:1,5), Rissen (I 6,7,14:f,g:�)

2002 3.1 Virchow 6,7:r:1,2 93 18.3 Infantis (I 6,7,14:r:1,5) (9), Colindale (I 6,7:r:1,7) (5), Galiema(I 6,7,14:k:1,2), Senegal (I 11:r:1,5), Thompson (I 6,7,14:k:1,5)

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Typhimurium that arose following loss of the phase two flagel-lin gene fljB (2).

Incorrect serovar identification was often caused by incor-rect detection of the phase two flagellar antigen. In many

instances, erroneous serotyping results differed from the ex-pected serovar only by the phase two flagellar antigen (Table1). Discrimination within the H antigen complexes (E, G, andL) also accounted for a significant number of errors.

TABLE 1—Continued


serotyping%


2002 3.2 Derby 4,12:f,g:� 91 7.1 Agona (I 1,4,�5�,12:f,g,s:�1,2�) (3), Essen (I 4,12:g,m:�), Fyris(I 4,�5�,12:l,v:1,2), Kiel (I 1,2,12:,p:�)

2002 3.3 Weltevreden 3,10:r:z6 91 7.7 Elisabethville (I 3,10:r:1,7) (3), Seegefeld (I 3,10:r,i:1,2), Ughelli(I 3,10:r:1,5), Weltevreden (I 3,10,�15�:r:z6), Wilmington (I 3,10:b:z6)

2002 3.4 Senftenberg 1,3,19:g,t:� 89 17.1 Westhampton (I 3,10,�15�,�15,34�:g,s,t:�) (6), Rideau (I 1,3,19:f,g:�) (2),Catanzaro (I 6,14:g,s,t:�), Kingston (I 1,4,�5�,12,27:g,s,t:�1,2�), Maiduguri(I 1,3,19:f,g,t:e,n,z15), Suberu (I 3,10:g,m:�), Salmonella spp.

2002 3.5 Typhimurium var. 5�

4,12:i:1,2 96 4.3 Agona (I 1,4,�5�,12:f,g,s:�1,2�), Choleraesuis (I 6,7:c:1,5), Kingston(I 1,4,�5�,12,27:g,s,t:�1,2�), Lagos (I 1,4,�5�,12:i:1,5)

2002 3.6 Manhattan 6,8:d:1,5 90 15.4 Dunkwa (I 6,8:d:1,7) (2), Isangi (I 6,7,14:d:1,5) (2), Muenchen(I 6,8:d:1,2:�z15�) (2), Blockley (I 6,8:k:1,5), Bovismorbificans(I 6,8,20:r,�i�:1,5), Duesseldorf (I 6,8:z4,z24:�), Kottbus (I 6,8:e,h:1,5),Newport (I 6,8,20:e,h:1,2:�z67�), Yovokome (I 8,20:d:1,5)c

2002 3.7 Enteritidis 9,12:g,m:� 95 9.2 Dublin (I 1,9,12;�Vi�:g,p:�) (2), Essen (I 4,12:g,m:�), Kapemba(I 9,12:l,v:1,7), Nitra (I 2,12:g,m:�), Seftenberg (I 1,3,19:g,�s�,t:�),Typhimurium (I 1,4,�5�,12:i:1,2), Salmonella spp.

2002 3.8 Bovismorbificans 6,8:r:1,5 91 4.4 Hindmarsh (I 8,20:r:1,5)b (4), Infantis (I 6,7,14:r:1,5), Hidalgo(I 6,8:r,�i�:e,n,z15), Kentucky (I 8,20:i:z6) Tallahassee (I 6,8:z4,z32:�)

2001 2.1 Agona 4,12:f,g,s:� 80 18.8 Derby (I 1,4,�5�,12:f,g:�1,2�) (7), Salmonella spp. (4), Kingston(I 1,4,�5�,12,27:g,s,t:�1,2�), California (I 4,12:g,m,t:�), Enteritidis(I 1,9,12:�f�,g,m,�p�:�1,7�), Essen (I 4,12:g,m:�)

2001 2.2 Dublin 1,4,12:f,g:� 79 34.2 Enteritidis (I 1,9,12:�f�,g,m,�p�:�1,7�) (14), Rostock (I 1,9,12:g,p,u:�) (3),Agona (I 1,4�5�,12:f,g,s:�1,2�) (2), Salmonella spp. (2), Derby(I 1,4,�5�,12:f,g:�1,2�), Moscow (I 1,9,12:g,q:�), Regent (I 3,10:f,g,�s�,�1,6�),Togo (I 4,12:l,w:1,6), Typhi (I 9,12,�Vi�:d:�), II Neasdenb

2001 2.3 Infantis 6,7:r:1,5 83 13.3 Virchow (I 6,7,14:r:1,2) (3), Salmonella spp. (3), Colindale (I 6,7:r:1,7),Lomita (I 6,7:e,h:1,5), Oritamerin (I 6,7:i:1,5), Thompson (I 6,7,14:k:1,5),Typhimurium (I 1,4,�5�,12:i:1,2)

2001 2.4 Kottbus 6,8:eh:1,5 78 38.0 Newport (I 6,8,20:e,h:1,2:�z67�) (12), Tshiongwe (I 6,8:e,h:e,n,z15) (11),Salmonella spp. (4), Ferruch (I 8:e,h:1,5)b (3), Hidalgo(I 6,8:r,�i�:e,n,z15), Kalumburu (I 6,8:z:e,n,z15), Stourbridge (I 6,8:b:1,6)

2001 2.5 Typhimurium 4,12:i:1,2 80 9.6 Salmonella spp. (2), Gloucester (I 1,4,12,27:i:l,w), Kiel (I 1,2,12:g,p:�),Lagos (I 1,4,�5�,12:i:1,5), Paratyphi A (I 1,2,12:a:�1,5�), Sandiego(I 4;�5�,12:e,h:e,n,z15)

2001 2.6 Newport 6,8:eh:1,2 79 17.7 Tshiongwe (I 6,8:e,h:e,n,z15) (8), Bardo (I 8,e,h:1,2)c (1), Salmonella spp.(2), Kottbus (I 6,8:e,h:1,5), Paratyphi B (I 1,4,�5�,12:b:1,2), Rechovot(I 8,20:e,h:z6), Saintpaul (I 1,4,�5�,12:e,h:1,2)

2001 2.7 Hadar 6,8:z10:enx 76 23.7 Tshiongwe (I 6,8:e,h:e,n,z15) (8), Salmonella subsp. (4), Istanbul(I 8:z10:e,n,x)c (1), Chailey (I 6,8:z4,z23:�e,n,z15�), Hadar (I 6,8:z10:e,n,x),Hidalgo (I 6,8:r,�i�:e,n,z15), Mapo (I 6,8:z10:1,5), Quiniela (I6,8:c:e,n,z15), Rechovot (I 8,20:e,h:z6)

2001 2.8 Enteriditis 9,12:g,m:� 76 15.8 Salmonella subsp. (3), Dublin (I 1,9,12;�Vi�:g,p:�) (2), Blegdam(I 9,12:g,m,q:�), Berta (I 1,9,12:�f�,g,�t�:�), Kottbus (I 6,8:e,h:1,5),Newport (I 6,8,20:e,h:1,2:�z67�), Seremban (I 9,12:i:1,5), Typhimurium(I 1,4,�5�,12:i:1,2), II Kuilsrivierb

2000 1.1 Typhimurium 4,5,12:i:1,2 36 8.3 Farsta (I 4,12:i:e,n,x), Lagos (I 1,4,�5�,12:i:1,5), Tumodu (I 1,4,12:i:z6)2000 1.2 Typhimurium 1,4,5,12:i:1,2 36 11.1 Gloucester (I 1,4,12,27:i:l,w) (2), Lagos (I 1,4,�5�,12:i:1,5), Saintpaul

(I 1,4,�5�,12:e,h:1,2)2000 1.3 Bredeney 1,4,12:l,v:1,7 37 29.7 Typhimurium (I 1,4,�5�,12:i:1,2) (3), Arechavaleta (I 4,�5�,12:a:1,7) (2),

Fyris (I 4,�5�,12:l,v:1,2) (2), Derby (I 1,4,�5�,12:f,g:�1,2�), Gloucester(I 1,4,12,27:i:l,w), Paratyphi B (I 1,4,�5�,12:b:1,2), (�):eh:1,5b

2000 1.4 Newport 6,8:eh:1,2 36 22.2 Tshiongwe (I 6,8:e,h:e,n,z15) (3), Bardo (I 8,e,h:1,2),b Braenderup(I 6,7,14:e,h:e,n,z15), Kottbus (I 6,8:e,h:1,5), Larochelle (I 6,7:e,h:1,2),I (�):eh:1,2,b I 6,7:eh:�b

2000 1.5 Saintpaul 1,4,12:eh:1,2 36 30.6 Chester (I 1,4,�5�,12:e,h:e,n,x) (3), Kaapstad (I 4,12:e,h:1,7) (2), Sandiego(I 4;�5�,12:e,h:e,n,z15) (2), Kisangani (I 1,4,�5�,12:a:1,2), Saintpaul(I 1,4,�5�,12:e,h:1,2), Tsevie (I 4,12:i:e,n,z15), I 4:e,h:e,nb

2000 1.6 Schwarzengrund 1,4,12,27:d:1,7 36 33.3 Stanley (I 1,4,�5�,12,27:d:1,2) (3), Schwarzengrund (I 1,4,12,27:d:1,7) (2),Canada (I 4,12,27:b:1,6), Derby (I 1,4,�5�,12:f,g:�1,2�), Eppendorf(I 1,4,12,27:d:1,5), Gloucester (I 1,4,12,27:i:l,w), Grumpensis(I 13,23:d:1,7), Cairo,b I 4:d:�b

2000 1.7 Heidelberg 1,4,12:r:1,2 35 31.4 Typhimurium (I 1,4,�5�,12:i:1,2) (2), Derby (I 1,4,�5�,12:f,g:�1,2�), Kisangani(I 1,4,�5�,12:a:1,2), Kottbus (I 6,8:e,h:1,5), Paratyphi B (I 1,4,�5�,12:b:1,2),Remo (I 1,4,12,27:r:1,7), Saintpaul (I 1,4,�5�,12:e,h:1,2), Schwarzengrund(I 1,4,12,27:d:1,7), Stanley (I 1,4,�5�,12,27:d:1,2), I (�):eh:1,2b

2000 1.8 Enteritidis 9,12:g,m:� 37 10.8 Berta (I 1,9,12:�f�,g,�t�:�), Blegdam (I 9,12:g,m,q:�), Bournemouth(I 9,12:e,h:1,2), Ndolo (I 1,9,12:d:1,5)

a Underlining indicates somatic factors determined by phage conversion (present only when the culture was lysogenized by the corresponding converting phage).b Serotype submitted with no official name or antigenic formula.c Not considered an error, since the serovar is subject to colonial form variation by the minor O antigen (O:61).



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The overall percentage of correctly serotyped isolates dif-fered by region. The highest numbers of errors were observedin Central Asia and the Middle East, where little improvementwas seen during the seven iterations (50% in 2001 and 55% in

2007). The number of participants in the Oceanic region hasbeen consistent (n � 4), and all four laboratories correctlyserotyped all eight strains in both 2001 and 2007. In SoutheastAsia, the percentage of correctly serotyped isolates increased

TABLE 2. Numbers of laboratories producing deviating results per year and regiona

Region Yr No. oflaboratories

No. ofstrains

serotyped

% of strainscorrectlyserotyped

Countries participating in any iteration

Africa 2001 6 37 73.0 Botswana, Cameroon, Central African Republic, Democratic Republic of Congo,Ivory Coast, Mauritania, Madagascar, Mauritius, Morocco, Senegal, SouthAfrica, Sudan, Tunisia, Uganda

2002 9 62 87.12003 11 70 71.42004 9 51 62.72006 16 95 71.62007 11 73 80.8

Asia and MiddleEast

2001 10 60 50.0 Egypt, India, Israel, Jordan, Kuwait, Lebanon, Oman, Saudi Arabia, Syria2002 5 30 83.32003 5 35 54.32004 5 33 54.52006 5 35 74.32007 5 40 55.0

Caribbean 2001 0 0 0 Barbados, Guatemala, Honduras, Jamaica, Suriname, Trinidad and Tobago2002 0 0 02003 3 18 61.12004 2 8 87.52006 3 14 78.62007 2 9 77.8

China 2001 4 32 96.9 China2002 3 24 100.02003 8 60 75.02004 7 46 78.32006 6 48 85.42007 10 80 91.3

Europe 2001 43 323 80.5 Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic,Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland,Ireland, Italy, Latvia, Lithuania, Luxembourg, Macedonia, Malta, Republic ofMoldova, The Netherlands, Norway, Poland, Romania, Serbia andMontenegro, Slovak Republic, Slovenia, Spain, Turkey, United Kingdom

2002 50 384 90.02003 60 401 84.82004 57 392 84.72006 52 403 86.42007 54 415 89.4

North America 2001 4 32 87.5 Canada, United States2002 2 16 100.02003 6 41 95.12004 8 55 81.82006 10 80 96.32007 12 94 97.9

Oceania 2001 4 30 100.0 Australia, New Caledonia, New Zealand, Papua New Guinea2002 6 43 93.02003 6 46 93.52004 5 38 97.42006 5 37 94.62007 4 32 100.0

Russia 2001 1 8 12.5 Belarus, Georgia, Russia, Ukraine.2002 1 8 62.52003 1 7 14.32004 4 26 69.22006 5 40 80.02007 8 51 80.4

Latin America 2001 11 78 57.7 Argentina, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Ecuador, Mexico,Panama, Paraguay, Peru, Uruguay, Venezuela2002 11 82 87.8

2003 13 83 75.92004 15 88 79.52006 13 84 84.52007 15 107 88.8

Southeast Asia 2001 15 113 54.0 Cambodia, Indonesia, Japan, Malaysia, Philippines, Singapore, South Korea, SriLanka, Taiwan, Thailand, Vietnam2002 12 90 92.2

2003 15 100 81.02004 17 130 81.52006 15 117 84.62007 19 140 91.4

a No data are available for 2000.



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significantly (P � 0.01), from 54% in 2001 to 92% in 2002, andremained consistently over 80% through 2007. In Latin Amer-ica, performance increased significantly (P � 0.01), from 58%in 2001 to 89% in 2007. Europe had the highest number ofparticipating laboratories, and the percentage of correctly se-rotyped isolates ranged from 81% in 2001, when 43 laborato-ries participated, to 89% (P � 0.01) in the 2007 iteration, when54 laboratories participated (Table 2).

DISCUSSION

Through training, reference testing services, technical sup-port, and hosting of scientists, WHO Global Salm-Surv hasbeen working to improve the laboratory capacity and therebythe data quality of WHO member states. The EQAS is one ofthe tools the program uses to assess the impact of its capacity-building efforts and to pinpoint areas for improvement.

The results from the first seven iterations of the WHOGlobal Salm-Surv EQAS, which to our knowledge is the largestexternal quality assurance program for the serotyping of Sal-monella species, indicate that the majority of participating lab-oratories worldwide are capable of correctly serotyping Sal-monella species. The number of participating laboratoriesincreased consistently from 2000 to 2007, demonstrating anincreased interest in quality assurance and an increased globalcapacity for Salmonella serotyping. However, fluctuations inthe performance of some laboratories were observed. Somelaboratories still do not meet the WHO Global Salm-Surv goalof performing serotyping on all eight strains with no more thanone incorrect result. Efforts at building laboratory capacity forserotyping should focus on those laboratories in the future andshould be directed at common difficulties.

Since test strains differ from year to year, an improvement inthe performance of participating laboratories can be evaluatedonly on the basis of the internal quality controls. The results ofquality control have remained fairly consistent during theseven iterations despite a large increase in the number ofparticipants. The selection of a common serovar (Salmonellaserovar Enteritidis) may have biased the results: this serovar isfrequently encountered, and many laboratories are proficientat its identification. Additionally, this is a monophasic serovar.We have shown that most incorrect results appear to be caused

by errors in the identification of phase two flagellar antigens.These factors might have contributed to the consistently highperformance observed for the Salmonella serovar Enteritidisstrain. Selection of a diphasic serovar may reduce this bias inthe future.

Our data suggest that several factors contributed to theobserved errors. Unpublished data from a needs assessment inthe EQAS 2007 iteration, where 82 laboratories (56%) com-pleted the survey, showed that nearly 1 out of 3 (30%) labo-ratories have limited access to high-quality antisera. Addition-ally, less-common serovars were included in some iterations(e.g., Salmonella enterica serovar Vinohrady [I 28:m,t:�]), andthe same needs assessment found that 26% of laboratories haddifficulty serotyping rare and unusual Salmonella strains. Fi-nally, there are important regional differences in laboratorycapacity. The needs assessment found that institutions in Af-rica, Asia and the Middle East, and Southeast Asia were morelikely to report difficulty obtaining antisera, especially for se-rotyping unusual Salmonella strains, than were institutions inother regions.

The decline in the proportion of serotypes correctly identi-fied in 2003 and 2004 was likely due to the selection of theSalmonella isolates (Table 3). In 2003 and 2004, laboratoriesneeded less-common antisera in order to fully serotype all ofthe EQAS isolates. After 2004, only more-common serovarswere included. The subsequent overall improvement in perfor-mance suggests that many laboratories have access only tocommonly available antisera. WHO Global Salm-Surv hasdemonstrated that the predominant Salmonella serotypes dif-fer between regions (3). Therefore, a broad selection of anti-sera for Salmonella surveillance is needed globally. WHOGlobal Salm-Surv continues to provide information to partic-ipants on where to purchase high-quality antisera and to sup-port many laboratories with antisera for surveillance purposes.

Many of the incorrect serotyping results were due to incor-rect identification of phase two flagellar antigens (Table 1).For example, common incorrect results included misidentifi-cation of Salmonella serovar Typhimurium (I 4,5,12:i:1,2) asSalmonella enterica serovar Farsta (I 4,5,12:i:e,n,x), Lagos (I4,5,12:i:1,5), or Tumodu (I 4,5,12:i:z6). All four serovars sharethe same O and phase one flagellar antigens but differ in theirphase two flagellar antigens.

Colonial form variation (the variable expression of minorantigens by different single-colony picks from the same strain)may occur with the expression of the O:61 antigen by someserogroup C2 serovars (10). Therefore, although the currentKauffmann-White scheme regards O:6,8 and O:8 serovar pairs,such as Salmonella serovars Newport (I 6,8:e,h:1,2) and Bardo(I 8:e,h:1,2), as distinct serovars, we allowed for colonial formvariations. We considered correct identifications for Salmo-nella serovars Newport, Kottbus, Hadar, Manhattan, and Bo-vismorbificans on the basis of the serogroup alone and ac-cepted as correct for those serovars, respectively, Salmonellaserovars Bardo, Ferruch, Istanbul, Yovokome, and Hind-marsh.

The results from the WHO Global Salm-Surv EQAS alsodemonstrate important regional differences in the serotypingresults for Salmonella species. Particular efforts should focuson Central Asia and the Middle East, but also on Africa,Russia, and the Caribbean, where a large proportion of the

TABLE 3. Numbers (and percentages) of participating laboratoriesthat correctly serotyped all eight Salmonella isolates in EQAS

(2000 to 2007) and total number of isolates correctlyserotyped per iteration

YrNo. (%) of laboratories per

iteration that correctlyserotyped all eight isolatesa

Total no. (%) of isolatescorrectly serotyped per

iterationb

2000 34 (92) 165 (76)2001 79 (82) 513 (72)2002 80 (81) 668 (91)2003 69 (54) 692 (80)2004 78 (61) 701 (81)2006 105 (81) 808 (85)2007 109 (78) 920 (88)Overall 554 (76) 4,467 (82)

a Does not include laboratories that serotyped fewer than eight isolates.b Includes all correctly serotyped isolates, disregarding the fact that some

participants attempted to serotype fewer than eight test strains.



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laboratories do not correctly serotype many of the strains.Addressing the regional differences will involve additionaltraining courses in selected regions.

WHO Global Salm-Surv is a platform that can assist WHOmember states to strengthen their core public health capacitiesunder the International Health Regulations (IHR, 2005) fordisease surveillance and response, which will in turn strengtheninternational public health security. WHO Global Salm-Survpromotes intersectoral collaboration among human health,veterinary, and food-related disciplines in food safety andother issues that arise at the human-animal interface. As theprogram continues to expand, it increasingly addresses re-gional training and support needs.

Conclusion. This study showed that there is a continuingneed to improve Salmonella serotyping and that this needappears to be greater in specific regions. Detection of thephase two flagellar antigen is one of the more profound bar-riers to obtaining a satisfactory serotyping result. Future train-ing efforts should be aimed at enhancing the ability to charac-terize the phase two flagellar antigen and disseminatinginformation on where to purchase high-quality antisera.

ACKNOWLEDGMENTS

We thank the technical staff at the National Food Institute forpreparing, testing, and shipping the strains; the staff of the participat-ing laboratories who contributed to this program; and the staff at theregional sites for further distributing the EQAS parcels.

REFERENCES

1. Bangtrakulnonth, A., S. Pornreongwong, C. Pulsrikarn, P. Sawanpanyalert,R. S. Hendriksen, D. M. Lo Fo Wong, and F. M. Aarestrup. 2004. Salmonella

serovars from humans and other sources in Thailand, 1993–2002. Emerg.Infect. Dis. 10:131–136.

2. Echeita, M. A., S. Herrera, and M. A. Usera. 2001. Atypical, fljB-negativeSalmonella enterica subsp. enterica strain of serovar 4,5,12:i:� appears to bea monophasic variant of serovar Typhimurium. J. Clin. Microbiol. 39:2981–2983.

3. Galanis, E., D. M. Lo Fo Wong, M. E. Patrick, N. Binsztein, A. Cieslik, T.Chalermchikit, A. Aidara-Kane, A. Ellis, F. J. Angulo, and H. C. Wegener.2006. World Health Organization Global Salm-Surv. Web-based surveillanceand global Salmonella distribution, 2000–2002. Emerg. Infect. Dis. 12:381–388.

4. Hendriksen, R. S., A. M. Seyfarth, A. B. Jensen, J. Whichard, S. Karlsmose,K. Joyce, M. Mikoleit, S. M. Delong, F. X. Weill, A. Aidara-Kane, D. M. LoFo Wong, F. J. Angulo, H. C. Wegener, and F. M. Aarestrup. 19 November2008. Results of use of WHO Global Salm-Surv external quality assurancesystem for antimicrobial susceptibility testing of Salmonella isolates from2000 to 2007. J. Clin. Microbiol. doi:10.1128/JCM.00894-08.

5. Herikstad, H., Y. Motarjemi, and R. V. Tauxe. 2002. Salmonella surveillance:a global survey of public health serotyping. Epidemiol. Infect. 129:1–8.

6. Humphrey, T. J. 2000. Public-health aspects of Salmonella infections, p.245–263. In C. Wray and A. Wray (ed.), Salmonella in domestic animals.CABI Publishing, Wallingford, England.

7. Mead, P. S., L. Slutsker, V. Dietz, L. F. McCaig, J. S. Bresee, C. Shapiro,P. M. Griffin, and R. V. Tauxe. 1999. Food-related illness and death in theUnited States. Emerg. Infect. Dis. 5:607–625.

8. Olsen, S. J., R. Bishop, F. W. Brenner, T. H. Roels, N. Bean, R. V. Tauxe, andL. Slutsker. 2001. The changing epidemiology of Salmonella: trends in se-rotypes isolated from humans in the United States, 1987-1997. J. Infect. Dis.183:753–761.

9. Petersen, A., F. M. Aarestrup, F. J. Angulo, S. Wong, K. Stohr, and H. C.Wegener. 2002. WHO Global Salm-Surv External Quality Assurance System(EQAS): an important step towards improving the quality of Salmonellaserotyping and antimicrobial susceptibility testing worldwide. Microb. DrugResist. 8:345–353.

10. Popoff, M. Y. 2001. Guidelines for the preparation of Salmonella antisera,6th ed. WHO Collaborating Centre for Reference and Research on Salmo-nella. Institut Pasteur, Paris, France.

11. Popoff, M. Y., and L. Le Minor. 2001. Antigenic formulas of the Salmonellaserovars, 8th ed. WHO Collaborating Centre for Reference and Research onSalmonella, Institut Pasteur, Paris, France.



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ACKNOWLEDGEMENTS

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REFERENCES

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318

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232

176

151

102

720

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14.3

27.9

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53.3

28.5

18.2

4.3

5.1

10.8

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2.6

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7.8

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3.6

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4.3

3.2

11.0

4.9

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0.5

5.7

10.2

1.6

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6.0

9.7

4.0

3.9

2.8

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4.3

3.2

1.1

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2.5

2.7

5.2

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0.7

2.0

5.3

2.8

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3.0

3.3

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1.6

1.3

1.0

4.3

1.7

2.6

2.9

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8.6

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10.9

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4.4

7.5

4.1

6.9

13.9

16.0

4.2

3.5

6.1

1.5

1.2

4.2

2.6

7.4

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1.5

1.8

0.4

6.3

6.4

8.9

8.1

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1.2

8.2

6.4

4.8

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1.7

0.8

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6.3

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3.9

5.7

4.6

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3.9

2.9

1.6

2.6

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1.9

1.0

0.4

0.5

2.5

2.4

2.3

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3.9

4.4

5.2

5.5

0.7

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0.9

0.8

0.7

2.4

2.9

1.7

1.4

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5.5

2.2

4.0

5.9

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2.0

1.0

3.3

2.9

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1.9

2.1

1.5

1.0

0.4

0.9

0.9

0.6

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1.3

0.5

2.7

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2.6

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3.8

2.6

2.2

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0.7

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1.6

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2.1

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2.9

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0.8

0.8

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0.5

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1.7

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1.6

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Typh

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21.0

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Article III

Antimicrobial resistance and molecular epidemiology of Salmonella Rissen from

animals, food products, and patients in Thailand and Denmark.

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Antimicrobial Resistance and Molecular Epidemiologyof Salmonella Rissen from Animals, Food Products,

and Patients in Thailand and Denmark

Rene S. Hendriksen,1 Aroon Bangtrakulnonth,2 Chaiwat Pulsrikarn,2 Srirat Pornreongwong,2

Henrik Hasman,1 Si Wook Song,3 and Frank M. Aarestrup1

Abstract

Recently we reported increases in both the number of Salmonella infections due to Salmonella Rissen inThailand and the isolation of this serovar from pork products in Thailand. The objectives of the present studywere to determine the genetic diversity and antimicrobial resistance of Salmonella Rissen isolates recoveredfrom humans, food products, and animals in Denmark and Thailand. Additionally, risk factors due to traveland consumption of specific food products were analyzed and evaluated. A total of 112 Salmonella Rissenisolates were included in this study from Thailand andDenmark. Thai isolates were recovered from humans,uncooked food, and ready-to-eat food. Danish isolates were obtained from humans (with and without ahistory of travel to Thailand prior to the infection), Danish pig or pork products, imported pig or porkproducts, turkeys, and animal feed. A total of 63 uniqueXbaI PFGEpatternswere observed. The predominantpattern was shared by 22 strains. Limited antimicrobial resistance was observed in the Danish strains, and ahigher degree of resistance was observed in strains originating from Thailand. Virtually all isolates wereresistant to tetracycline. The tetA gene was detected in tetracycline-resistant isolates. Statistical analysis andmolecular subtyping identified the combination of travel to Thailand and consumption of imported pig orpork products as well consumption of as pig or pork products produced in Denmark as risk factors forSalmonella Rissen infection among the Danish patients. The outcome of this study might be used as a sup-plement for future Salmonella Rissen investigations and outbreak detection.

Introduction

Salmonella enterica is a common cause ofhuman gastroenteritis and bacteremia and a

wide variety of animals, particularly food ani-mals, have been identified as reservoirs for non-Typhi Salmonella (Coyle et al., 1988; Humphreyet al., 1988, 2000). Although 2587 serovars of Sal-monella enterica have been identified, most hu-man infections are caused by a limited number

of serovars. In developed countries, Salmonellaenterica serovars Typhimurium and Enteritidisare the most common causes of human salmo-nellosis, although other serovars have been re-ported to be more prevalent in specific regions(Humphrey et al., 2000; Olsen et al., 2001; Her-ikstad et al., 2002; Bangtrakulnonth et al., 2004b;Galanis et al., 2006). Shifts in prevalence of spe-cific strain types and serovars can be due tointernational travel, human migration, and a

1WHO Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and EU Community Reference Laboratory forAntimicrobial Resistance, National Food Institute, Technical University of Denmark, Copenhagen, Denmark.

2WHO International Salmonella and Shigella Centre, National Institute of Health, Department of Medical Sciences, Ministry of PublicHealth, Bangkok, Thailand.

3The National Veterinary Research and Quarantine Service, Anyang, Korea.

FOODBORNE PATHOGENS AND DISEASEVolume 5, Number 5, 2008ª Mary Ann Liebert, Inc.DOI: 10.1089=fpd.2007.0075

605

global food and livestockmarket. Knowledge ofthe prevalence and molecular epidemiology ofdifferent serovars in specific regions may facili-tate the recognition and control of new andemerging pathogens.

We recently reported an increase in Salmonellainfections due to Salmonella enterica serovar Ris-sen in Thailand. The reported number of humanSalmonella infections due to Salmonella Rissen inThailand has increased from 54 cases in 1993 to334 in 2002. During that same time period, a 10percentage point increase (4.7% to 14.7%) in theisolation of Salmonella Rissen from specific foodproducts was also observed (Bangtrakulnonthet al., 2004b).While this serovar is rarely reportedelsewhere in the world, it is among the top threeSalmonella serovars found in pigs and porkproducts in Thailand, other Southeast Asiancountries, and Spain (Bangtrakulnonth et al.,2003, 2004a, 2005; Angkititrakul et al., 2005;Vaeteewootacharn et al., 2005; VAV, 2005; In-thavong et al., 2006; Padungtod and Kaneene,2006; Riano et al., 2006; Vo et al., 2006; Astorgaet al., 2007).

In recent years, increased antimicrobial resis-tance has been reported in several serovars ofS. enterica. However, only limited data on theprevalence of antimicrobial resistance of Salmo-nella Rissen is available. In 2005, Angkititrakulreported tetracycline, streptomycin, and sul-phonamide resistance among Salmonella Rissenisolates recovered from pork and chicken inThailand. The isolates recovered fromporkwerehowever susceptible to ciprofloxacin, gentami-cin, chloramphenicol, amoxicillin, and sulpha-methoxazoleþ trimethroprim (Angkititrakulet al., 2005). In contrast, multidrug-resistant iso-lates of Salmonella Rissen have been reportedfrom Spain. Previous studies have shown theseisolates to be resistant to ampicillin, amoxy-cillin, streptomycin, neomycin, sulphonamides,sulphanamidesþ trimethoprim, chlorampheni-col, and tetracycline (Riano et al., 2006; Astorgaet al., 2007). One study (Riano et al., 2006) alsodescribed the identification of the blaSHV-12

gene in a cefotaxime and ceftazidime resistantisolate.

Antimicrobial susceptibility profiles and mo-lecular subtyping are useful epidemiologicaltoolswhich can be used to determine the sourcesof an outbreak. To our knowledge, only one

molecular study of Salmonella Rissen has previ-ously been undertaken. In this earlier study 19Portuguese isolates of Salmonella Rissen werecharacterized bypulsed-field gel electrophoresis(PFGE). Three unique XbaI patterns were ob-served, with the predominant pattern beingshared by 17 isolates (Vieira-Pinto et al., 2006).The objectives of the present study were to

determine the genetic diversity and antimicro-bial resistance of Salmonella Rissen isolates re-covered from humans, food products, andanimals in Denmark and Thailand.Microbiological findingswere correlatedwith

epidemiological data, and risk factors for infec-tion with Salmonella Rissen were calculated.The outcome of this study might be used as a

supplement for future Salmonella Rissen inves-tigations and outbreak detection.

Methods

Bacterial isolates

The WHO National Salmonella and ShigellaCentre in Bangkok receives all presumptivepositive Salmonella isolates from all diagnosticlaboratories throughout Thailand. In 2004, 300isolates were identified as SalmonellaRissen. Theisolates originated from 9 of 12 districts andBangkok.In addition to human isolates, The WHO Na-

tional Salmonella and Shigella Centre also re-ceives isolates recovered from food products. In2004, the centre received 295 isolates, originatingfrom various food sources. The majority of theisolates originated from pork products. Thesesamples were further characterized as ‘‘rawfood’’ (n¼ 128) or ‘‘ready-to-eat food’’ (n¼ 92).The raw food isolates were submitted from dis-tricts 1, 3, and 4 and Bangkok over a 1-year pe-riod, excluding the months of February to Apriland October to December. The isolates origi-nating from ready-to-eat food were collectedover a 9-month period (April–December) fromdistricts 1 and 10 and Bangkok.The 23 human isolates from Denmark were

collected between 2000 and 2005 by theNationalReference Laboratory for EnteropathogenicBacteria, Statens Serum Institut (SSI) in Den-mark. These isolates were recovered from pa-tients suffering from gastrointestinal infectionscaused by Salmonella Rissen. Four cases were

606 HENDRIKSEN ET AL.

acquired in Denmark. Six patients had traveledto Thailand prior to becoming ill. Travel historywas unavailable for the remaining 13 cases. Anadditional 155 isolates were identified by theNational Food Institute,Copenhagen,Denmark.These isolates were obtained from pig or porkproducts of Danish origin (n¼ 61), imported pigor pork products (n¼ 19), turkey (n¼ 19), andanimal feed (n¼ 24). The remaining 32 isolateswere either from an unknown source or origi-nated from caged birds, chickens, the environ-ment, horses, cattle, or bone meal. All isolateswere collected between 1996 and 2005.

The isolates were initially identified as Sal-monella spp. according to internationally recog-nized procedures. Isolates were then serotypedusing slide agglutination in the countryof origin.

Selection of isolates

Usingastratifiedrandomsampling technique,33 of the 300 human isolates fromThailandwereselected for additional characterization. Isolateswere from both male and female patients resid-ing in districts 1, 4, 5, 7, 8, and 12 and Bangkok.Patients ranged in age from 1 to 42 years. A re-view of the sample collection date was used toinsure that the isolateswere representative of thestudy period. The isolates from the raw food andready-to-eat food were selected from the sametime period as the Thai human isolates. Themajority of the food isolates were recovered inMay and June.

Thirteen of the 128 raw food isolates were se-lected for additional characterization. The se-lected isolates were from districts 1, 3, and 4 andBangkok. Ten of the ninety-two isolates fromready-to-eat food were selected for additionalcharacterization. The selected isolateswere fromdistrict 1 and Bangkok.

All 23 human isolates from Denmark wereincluded in the study. A stratified randomsampling technique was used to select isolatesfrom the NFI collection for additional charac-terization.

Isolates selected for additional characteriza-tion were obtained from: Danish pigs and porkproducts collectedbetween2002 to 2005 (n¼ 10);imported pig or pork products (Spanish originn¼ 5, German origin n¼ 1, unknown originn¼ 3) submitted to Danish import control au-

thorities between 2002 and 2005 (n¼ 9); turkeycollected between 2000 and 2002 (n¼ 6); andanimal feed collected between 2001 and 2005(n¼ 8).

Risk factors

SAS version 9.1.3 (SAS Institute Inc., Cary,NC) was used to calculate the relative risk usinga Fisher’s Exact test. The risk of disease for con-sumption of imported pork from Spain and therisk factor of travel to Thailand among theDanish patients infected with Salmonella Rissenwere evaluated.

Serotyping

O and H antigens were characterized byagglutination with hyperimmune sera and sero-type was assigned according to the Kauffmann–White scheme (Popoff and Le Minor, 2001).

Antimicrobial susceptibility testing

Susceptibility to antimicrobial agents wasperformed at the NFI on all selected isolates asminimum inhibitory concentration determina-tions using a commercially prepared, dehy-dratedpanel (Sensititre�) fromTREKDiagnosticSystems Ltd. (East Grinstead, England).The following antimicrobials and resistance

cut-off values or breakpoint were used in thestudy: ampicillin, AMP (R> 4 mg=mL); amoxi-cillinþ clavulanic acid, AUG (R> 4 mg=mL);apramycin, APR (R> 16mg=mL); cefalothin,CEF (R> 16mg=mL); cefpodoxime, POD (R> 1mg=mL); ceftiofur, XNL (R> 2 mg=mL); chlor-amphenicol, CHL (R> 16mg=mL); cipro-floxacin, CIP (R> 0.06mg=mL); colistin COL(R> 8 mg=mL); florfenicol, FFN (R> 2 mg=mL);gentamicin, GEN (R> 2 mg=mL); nalidixic acid,NAL (R> 16mg=mL); neomycin, NEO (R> 8mg=mL); spectinomycin, SPE (R> 64 mg=mL);streptomycin, STR (R> 16 mg=mL); sulpha-methoxazole, SMX (R> 256 mg=mL); tetracy-cline, TET (R> 8 mg=mL); and trimethoprim,TMP (R> 2mg=mL).Epidemiological cut-off values were inter-

preted according to current eucast (http:==www.eucast.org) and European Food SafetyAuthority (EFSA) recommendations. Exceptionsweremade for interpretationofAPR,AUG,CEF,

CHARACTERIZATION OF SALMONELLA RISSEN 607

COL, FFN, POD, SPE, and XNL, where Clinicaland Laboratory Standards Institute (CLSI, 2002,2006a, 2006b)guidelinesandclinicalbreakpointswere utilized. NEO and STR were interpretedaccording to research conduced at NFI. Qualitycontrol using E. coliATCC 25922was conductedon a weekly basis according to CLSI.

Detection of resistance genes

Resistant and intermediate strains were fur-ther characterized through the use of a poly-merase chain reaction (PCR) assay with primersspecific for 25 antimicrobial resistance genes(Table 1).

All PCR amplifications were performed withbuffer supplied by the manufacturer, 20 pmol=mL of each primer and 0.5 U of Amplicon TaqPolymerase (Ampliqon,Copenhagen,Denmark).The final reaction volume was (50mL), The fol-lowing cycling conditions were used for all re-actions: 3minutes at 948C; 35 cycles of 1minute at948C, 1 minute at the appropriate annealingtemperature, and 1minute at 728C; 10minutes at728C. Primer names and sequences, resistancegenes, primer position, annealing temperature,control strains, amplicon sizes, and references arelisted in Table 1.

Amplicons produced by the seven CIP-resistant strains and the single blaCTX amplicongenerated,were selected for sequencing. Prior tosequencing, the amplicons were purified usingthe GFX� PCR DNA kit (Amersham Bios-ciences, Piscataway, NJ), The DNAwas shippedto Macrogen Inc. (Seoul, Korea) for sequencingusing the same primers as in the PCR analysis.Sequence analysis and alignment was per-formedusingVectonNTI suite 9 (InforMax, Inc.,Bethesda, MD) software. The resulting nucleo-tide sequences were compared to sequencesobtained from the GenBank database (http:==www.lahey.org =studies=webt.html).

Pulsed-field gel electrophoresis

The selected isolateswere analyzed for geneticrelatedness by PFGE usingXbaI according to theCenters for Disease Control and Prevention(CDC) PulseNet protocol (Ribot et al., 2002). Theelectrophoresis was performedwith a CHEFDRIII System (Bio-Rad Laboratories, Hercules,CA) by using 1% SeaKem agarose in 0.5�Tris-

borate-EDTA at 180 V. Running conditionsconsisted of 1phase from2.2 to 63.8 seconds for arun time of 22 hours.PFGE following digestion with BlnI was uti-

lized to further differentiate the 22 isolateswhich exhibited the predominant XbaI pattern(TEEX01.0017.DK). Comparison of the PFGEprofiles was performed by using Bionumericssoftware version 4.6 (Applied Maths, Sint-Martens-Latem, Belgium) and the dice correla-tion for band matching with a 1.0% positiontolerance andanoptimization at 1.0%usingbothXbaI and BlnI.

Results

Risk factors

Available travel histories suggested that sixDanish patients (5%) may have acquired theirinfection abroad and four patients (4%) mayhave obtained the infection in Denmark. All sixpatients (5%) who traveled to Thailand shared acommon PFGE pattern with a Thai isolate. Six(5%) of the remaining 17 patients (15%) did notshare a common PFGE pattern. Among theDanish patients, there did not appear to be astatistically significant connection using Fisher’sExact test ( p¼ 0.1438) between travel to Thai-land (exposure) and sharing a common PFGEprofile with a Thai source (outcome).Nine isolates (8%) included in the study

originated from imported pig or pork products.Six of these isolates (5%) shared a commonPFGE pattern with a Danish patient. Three (3%)of the ten Danish pig or pork product samples(9%) included in this study shared a commonPFGE pattern with a Danish patient. The risk ofconsuming imported pig or pork (exposure)was estimated between pork or pig and shar-ing a common PFGE profile with Danish pa-tients who had not traveled prior to the onsetof infection (outcome). No statistical signifi-cance was observed using Fisher’s Exact test( p¼ 0.3469).

Antimicrobial resistance

All eight (7%) isolates from animal feed orig-inating from Denmark were fully susceptible toall antimicrobials tested. A similarly low fre-quency of resistance was observed in six (5%)


Table1.

OligonucleotidePrimerSequencesUsedfortheAmplification

oftheVariousResistanceGenes

Antimicrobial

family

Resistant

gene

Primer

nam

ePrimer

no.

Sequence

Position

Annealing

temp.(8C)

Control

strain

Amplicon

size

(bp)

Reference

Beta-lactam

sbla

CTX

ctx-M

-9P1

1096

50-G

TG

ACA

AAG

AGA

GTG

CAA

CGG-3

085–105

Salmonella

Virch

ow

ctx-M

-9P2

1097

50-A

TG

ATTCTC

GCC

GCTGAA

GCC-3

0941–921

6075-22438-1

857

Costaet

al.,2006

Beta-lactam

sbla

CTX

ctxM

U1

1354

50-A

TG

TGC

AGY

ACC

AGTAAR

GTK

ATG

GC-3

0211–236

Salmonella

Virch

ow

Hasman

etal.,2005;Miroet

al.,

ctx-M

-U2

1355

50-TGG

GTRAARTARGTSACC

AGA

AYC

AGC

GG-3

0803–775

6075-22438-1

593

2002;Archam

bau

ltet

al.,2006

Beta-lactam

sbla

TEM

TEM-C

-R-ny

686

50-A

CC

AATGCTTAA

TCA

GTG

AG-3

02671–2652

Salmonella

ParatyphiB

Assev

aet

al.,2006

Pbr322

tem

1Aprimer

2690

50-C

GC

ATA

CAC

TATTCTCAG

AATG-3

02086–2107

50TEM20

586

Patersonet

al.,2003

Aminoglycosides

aac(3@)-IV

AME14ACC(3)IV

B152

50-A

GTTGA

CCC

AGG

GCTGTC

GC-3

0938–919

E.coli

May

nardet

al.,2003

AME13ACC(3)IV

F153

50-G

TG

TGC

TGC

TGG

TCC

ACA

GC-3

0311–330

63K13

AAC(3)-IV

627

May

nardet

al.,2003

Aminoglycosides

aac(2@)-I

AME3,

ANT(2@)-I-1

8150-G

GG

CGC

GTC

ATG

GAG

GAG

TT-3

01491–1510

E.coli

AME4,

ANT(2@)-I-2

8250-TATCGC

GAC

CTG

AAA

GCG

GC-3

01819–1800

67K2ANT(2@)-I

329

Cam

eronet

al.,1986

Aminoglycosides

aac(3@)-II

AME7,

AAC(3)-II

X51534381->400

8750-TGA

AAC

GCTGAC

GGA

GCC

TC-3

0471–490

Klebsiella

AME8,

AAC(3)-II

X51534750->731

8850-G

TC

GAA

CAG

GTA

GCA

CTG

AG-3

0840–821

55K8AAC(3)-II

370

Vlieg

enthartet

al.,1989

Aminoglycosides

aph(3@)-III

P2,

APH(3@)-III

203

50-G

CC

GATGTG

GATTGC

GAA

AA-3

0454–473

Enterococci

Lim

etal.,2006;

P1-APH(3@)-IIInew

1428

50-G

CTTGA

TCC

CCA

GTA

AGTCA-3

0745–726

52JH

2-1-5APH

(3@)-III

292

Udoet

al.,2002

Aminoglycosides

aph(3

0 )-I

AME19

APH

(30 )I-F

171

50-A

AC

GTC

TTG

CTC

GAG

GCC

GCG-3

01182–1202

optained

amplicons

AME20

APH(3

0 )I-B

172

50-G

GC

AAG

ATC

CTG

GTA

TCG

GTC

TGC

G-3

01851–1828

68670

Okaet

al.,1981

Aminoglycosides

aph(3@)-II

AME21

Aph30-II-F

186

50-G

CTATTCGG

CTA

TGA

CTG

GGC-3

0768–788

optained

amplicons

AME22

APH

(30 )-IIB

187

50-C

CA

CCA

TGA

TATTCG

GCA

AGC-3

01309–1289

60542

Aarestrupet

al.,2003

Phen

icols

catA

1CAT1,X64410a

193-213

9450-C

GC

CTG

ATG

AATGCTCATCCG-3

0569–580

Salmonella

Typhim

urium

CAT2,X64110a,649-630

9550-C

CTGCC

ACTCATCGC

AGTAC-3

0126–145

60DS611

455

Aarestrupet

al.,2003

Phen

icols

cmlA

CmlA

1F,U123383860¼>

3879

114

50-TAC

TCG

GATCCA

TGC

TGG

CC-3

02028–2047

Salmonella

Typhim

urium

CmlA

2B,U123384437¼>

4418

115

50-TCC

TCG

AAG

AGC

GCC

ATTGG-3

02586-2605

65DS611

578

Inthis

study

Phen

icols

floR

PO_F

LOR_N

Y398

50-C

AG

CTTGGTCTTCAA

CTG

CA-3

0353–372

Salmonella

Typhim

urium

Flor-3-rev.

437

50-A

CG

GAC

ACC

GTG

AAG

ACA

AT-3

01024–1043

60DS611

691

Inthis

study

Quinolones

gyr

AgyrA

,P2bio

184

50-TAC

CGTCATAGTTATCCA

CGA-3

0305–325

Salmonella

gyrA

,P3

185

50-G

TA

CTTTAC

GCC

ATG

AAC

GT-3

013–32

60P502212

313

Wiuffet

al.,2000

Aminoglycosides

strA

Strep

-res,strA

,plasm

-

ref1010,787-769,primer-2

6750-C

CA

ATC

GCA

GATAGA

AGG

C-3

787–769

E.coli

Strep

-res,strA

,plasm

-

ref1010,240-259,primer-1

6850-C

TTGGTGATAAC

GGC

AATTC-3

0240–259

55RF1010

548

Aarestrupet

al.,2003

Aminoglycosides

strB

Strep

-res,strB,plasm

-ref1010,

623-604,

primer-2

6550-G

GA

TCG

TAG

AAC

ATA

TTG

GC-3

0623–604

E.coli

Strep

-res,strB,plasm

-ref1010,

115-134,

primer-1

6650-A

TC

GTC

AAG

GGA

TTG

AAA

CC-3

0115–134

56RF1010

509

Sch

olz

etal.,1989

Aminoglycosides

aadA

aadA

forw

ard

521

50-A

TTTGC

TGG

TTA

CGG

TGA

CC-3

0234–253

Salmonella

aadA

backward

522

50-C

TTCAA

GTC

TGA

CGG

GCTGA-3

0748–767

56P502212

534

Inthis

study

Quaternary

ammonium

compounds

qacE

D1

des-1

847

50-A

TC

GCA

ATA

GTTGGC

GAA

GT-3

02529–2548

Salmonella

Typhim

urium

des-2

848

50-C

AA

GCTTTTGCC

CATGAA

GC-3

02735–2754

57DS611

226

San

dvan

get

al.,1997

Sulfonam

ides

sulI

Sul1forw

ard

519

50-TGA

GATCAG

ACG

TATTGC

GC-3

02875–2894

Salmonella

Sul1backward

520

50-TTG

AAG

GTTCGA

CAG

CAC

GT-3

03261–3280

58P502212

406

Inthis

study

Sulfonam

ides

sulII

Sul2-f

591

50-G

CG

CTC

AAG

GCA

GATGGC

ATT-3

0154–174

Salmonella

Typhim

urium

Sul2-b

592

50-G

CG

TTTGATACC

GGC

ACC

CGT-3

0418–438

68B(Sul2)

285

Aarestrupet

al.,2003

Sulfonam

ides

sulIII

sul3(F)

1356

50-G

AG

CAA

GATTTTTGG

AATCG-3

02981–3000

Salmonella

Typhim

uium

sul3(B)

1357

50-C

ATCTG

CAG

CTA

ACC

TAG

GGC

TTTGGA-3

03770–3753

51C(Sul3)

773

Perretenan

dBoerlin,2003

Tetracycline

tetA

TetA

primer1

173

50-G

TA

ATTCTG

AGC

ACTGTC

GC-3

01084–1103

E.coli

Aarestrupet

al.,2003;

TetA

primer2

175

50-C

TG

CCTGGA

CAA

CATTGC

TT-3

02021–2040

57NCTC

50078

957

Waterset

al.,2003

Tetracycline

tetB

TetB-Tn10¼,

39->

5890

50-C

TC

AGTATTCCA

AGC

CTTTG-3

039–58

E.coli

Aarestrupet

al.,2003;

TetB-Tn10¼,

454->434

9150-A

CTCCC

CTG

AGC

TTG

AGG

GG-3

0454–434

52CSH50::T

n10

415

Sen

geløvet

al.,2003

Tetracycline

tetC

TetC,595->

576

9250-G

GTTGA

AGG

CTC

TCA

AGG

GC-3

0595–576

E.coli

Aarestrupet

al.,2003;

TetC,90->110

9350-C

CTCTTGCG

GGA

TATCGTCC-3

090–110

62DO7pBR322

506

Sen

geløvet

al.,2003

Tetracycline

tetD

Tet

D2(894-874)

575

50-C

ATCCA

TCC

GGA

AGTGATAGC-3

0894–874

E.coli

Aarestrupet

al.,2003;

Tet

D1(459-478)

576

50-G

GA

TATCTC

ACC

GCA

TCTGC-3

0459–478

57C600=psL

106

436

Miran

daet

al.,2003

Tetracycline

tetG

TetA(G

)-1

229

50-G

CA

GCG

AAA

GCG

TATTTG

CG-3

029–48

Salmonella

TetA(G

)-2

230

50-TCC

GAA

AGC

TGTCCA

AGC

AT-3

0672–691

60P502212

663

Aarestrupet

al.,2003

Table2.

Origin

andFrequencyofResistanceAmongSalmonellaRissen

Isolatesfrom

VariousSourcesin

DenmarkandThailand

No.

(%)of

resistantisolates

against

thelisted

antimicrobials

Country=Source

No.

(%)of

isolates

AUG

AMP

APR

CEF

POD

XNL

CHL

CIP

FFN

GEN

NAL

NEO

SPE

STR

SMX

TET

TMP

Den

mark

Patientsa,b

17(15)

02(12)

01(6)

1(6)

1(6)

1(6)

1(6)

00

1(6)

02(12)

2(12)

2(12)

14(82)

2(12)

Turism

e(Thailand)

6(5)

03(50)

00

00

2(33)

1(17)

00

1(17)

1(17)

1(17)

3(50)

1(17)

6(100)

1(17)

Turkey

c6(5)

00

00

00

00

00

00

01(17)

01(17)

0

Anim

alfeed

8(7)

00

00

00

00

00

00

00

00

0

Pig=Pork

10(9)

02(20)

00

00

00

00

01(10)

2(20)

2(20)

2(20)

8(80)

2(20)

Imp.Pork

9(8)

02(22)

1(11)

00

00

00

1(11)

00

2(22)

3(33)

3(33)

9(100)

1(11)

Thailand

Patients

33(30)

012

(36)

01(3)

00

9(27)

5(15)

1(3)

2(6)

5(15)

4(12)

11(33)

9(27)

10(30)

29(88)

9(27)

Ready-to-eat

food(Pork)

10(9)

03(30)

00

1(10)

02(20)

01(10)

00

2(20)

3(30)

1(10)

3(30)

8(80)

3(30)

Raw

food(Pork)

13(12)

05(38)

00

00

2(15)

00

00

05(38)

2(15)

5(38)

10(77)

5(38)

aIncludingoneisolate

from

apremature

infantthat

was

resistan

tto

AMP,CEF,POD,XNL,CHL,SPE,STR,SMX,TET,an

dTMP.

bTravel

histories

wereav

ailable

for9=

23Dan

ishpatients.

c sam

plesinclude:

meat,an

imal

feed

andlivean

imals.

AMP,am

picillint;AUG,am

oxicillinþ

clav

ulanic

acid;APR,ap

ramycin;CEF,cefalothin;POD,cefpodoxim

e;XNL,ceftiofur;CHL,ch

loramphen

icol;CIP,ciprofloxacin;FFN,florfen

icol;GEN,

gen

tamicin;NAL,nalidixic

acid;NEO,neo

mycin;SPE,sp

ectinomycin;STR,streptomycin;SMX,su

lpham

ethoxazole;TET,tetracycline;

TMP,trim

ethoprim.

isolates from turkey slaughtered in Denmarkand 10 (9%) isolates from pig or pork productsproduced in Denmark (Table 2).

Danish-produced pig or pork product isolatesand isolates from imported pig or pork productshad a higher frequency of resistance to TET(80.0 %).

Ahigher frequencyof resistancewasobservedin the six isolates (5%) cultured from Danishpatients with a history of travel to Thailandcompared to the 17 isolates (15%) from Danishpatients. Resistance to CHL, CIP, NAL, NEO,SPE, SMX, and TMP ranged from 17% to 33%. Ahigher frequency of resistancewas seen toAMP,STR, and TET with 50%, 50%, and 100% resis-tance observed, respectively.

The human isolates from Thailand showedhigh resistance to AMP (36%), CHL (27%), SPE(33%), STR (27%), SMX (30%), and TMP (27%).The majority of isolates (88%) were fully resis-tant to TET.

The isolates from raw food and ready-to-eatfood showed similar trends in the frequency ofresistance. High level of resistance was seenagainst TET (77–80%) (Table 2). One humanisolate from Denmark found to be multidrugresistant: AMP, CEP, POD, XNL, CHL, SPE,STR, SMX, TET, and TMP. However, this strainwas recovered from a premature infant whomost likely had received treatment with anti-microbials.

Identification of resistance genes

TetA specific amplicons were produced by allTET-resistant isolates (18%) obtained fromDanish patients; including those with a historyof travel to Thailand (8%), pork imported fromSpain or Germany (7%), ready-to-eat food (9%),and raw food from Thailand; and five isolatesfrom Danish pig or pork products (4%). Thethree isolates (3%) from Danish pig or porkproducts, and one isolate (1%) from turkey alsoyielded tetB specific amplicions (Table 3).

All SMX-resistant isolates (2%) obtained fromDanish patients produced amplicons specific tosul1. The SMX-resistant isolate (1%) fromDanishpatient with a history of travel to Thailand pro-duceda sul3 specific amplicon. Two isolates (2%)from Danish pig or pork product samples pro-duced sul1 and sul2 specific amplicons, respec-

tively. The three isolates (3%) from imported pigor pork products and the ready-to-eat (3%) andraw food (4%) samples from Thailand producedamplicons to sul1 and sul3 (Table 3).A single base-pair substitution in the gyrA

gene was identified in seven CIP-resistantstrains (7%). Five of these strains (4%) originatedfrom Thai patients and two (2%) from Danishpatients, one (1%) of whom had travelled toThailand. Isolates from three of the Thai patients(3%) and one of the Danish patients (1%) had amutation at codon 83 (TCC [Ser]?TTC [Phe]).The two remaining Thai patients (2%) and theDanish patient (1%) (who had travelled toThailand) had a mutation at codon 87 (GAC[Asp]?AAC [Asn]). (Mutated bases are shownin bold.)The isolate from the Danish patient which

produced a positive amplicon to blaCTX was se-quenced and showed 100% similarity to strainsin the GenBank encoding for blaCTX-M-14.

PFGE typing

A total of 63 unique XbaI patterns; were ob-served among the 112 isolates (Fig. 1). These 63patterns formed 10 distinct clusters. All isolatesfrom Danish patients with a history of travel toThailand (n¼ 6) shared XbaI patterns with iso-lates recovered in Thailand. Five of these isolatesmatched patterns obtained from isolates recov-ered from raw food or ready-to-eat food sam-ples in Thailand. The predominant patternTEEX01.0017.DK belonged to PFGE cluster 4and consisted of 22 (20%) isolates. This XbaIcluster included: five isolates (4%) from Thaipatients; three isolates (3%) from ready-to-eatfood; two isolates (2%) from raw food; six iso-lates (5%) from Danish patient, two (2%) ofwhom had traveled to Thailand; four isolates(4%) from imported pig or pork products (n¼ 3from Spain and n¼ 1 from Germany), and twoisolates (2%) originating from Danish pig orpork products. When pattern TEEX01.0017.DKwas further subtyped using the BlnI enzyme, sixpatterns (TEEA26.0001.DK–TEEA26.0006.DK)were obtained (Fig. 2). The predominant patternTEEA26.0001.DK was shared by 17 isolates(15%) including: six isolates (5%) from Danishpatients, two (2%) of whom had traveled toThailand; one pig or pork product isolate (1%)


Table3.

Distribution

ofAntimicrobialResistanceGenesin

SalmonellaRissen

Isolatesfrom

DifferentSources

No.

(%)of

isolates

foreach

gene

Tetracycline

Cloramphenicol

Florphenicol

Neomycin

Gentamicin

Quinolones

Streptomycin

Spectinom

ycin

&Streptomycin

Sulfam

ethoxazole

Quatem

ary

ammonium

compounds

(QAC)

Ampicillin

Ceftiofur

Country=S

ource

tetA

tetB

tetC

tetD

tetG

cmlA

catA1

floR

aph(3@)-III

aph(3@)-IIaph(3@)-I

aac(3@)-IV

ent(2@)-II

aac(3@)-II

gyrA

strA

strB

aadA

sul1

sul2

sul3

qacE

D1

bla T

EM

bla C

TX

Den

mark

Patients

fg.

14=14

(100)0=

14(0)

0=14

(0)0=14

(0)0=

14(0)

0=2(0)

2=2(100)

——

——

——

—1a=1(100)

0=3(0)

0=3(0)

2=3(67)

2=2(100)

0=2(0)

0=2(0)

2=2(100)

1=2(50)

1d=1(100)

Turism

e

(Thailand)

6=6(100)

0=6(0)

0=6(0)

0=6(0)

0=6(0)

1=1(100)

1=1(100)

0=1(0)

0=1(0)

1=1(100)

0=1(0)

——

—1b=1(100)

2=4(50)

2=4(50)

1=4(25)

0=1(0)

0=1(0)

1=1(100)

0=1(0)

3=3(100)

—

Turkey

@0=

1(0)

1=1(100)

0=1(0)

0=1(0)

0=1(0)

——

——

——

——

——

1=2(50)

1=2(50)

0=2(0)

——

——

——

Anim

alfeed

——

——

——

——

——

——

——

——

——

——

——

——

Pig=Pork

5=8(63)

3=8(37)

0=8(0)

0=8(0)

0=8(0)

——

—0=

1(0)

1=1(100)

0=1(0)

——

——

2=5(40)

1=5(20)

2=5(40)

1=2(50)

1=2(50)

0=2(0)

2=2(100)

2=2(100)

Imp.Pork

9=9(100)

0=9(0)

0=9(0)

0=9(0)

0=9(0)

——

——

——

1=1(100)

0=1(0)

0=1(0)

—2=

4(50)

2=4(50)

2=4(50)

1=3(33)

0=3(0)

2=3(66)

1=3(33)

2=2(100)

Thailand

Patients

29=29

(100)0=

29(0)

0=29

(0)0=29

(0)0=

29(0)5=

11(45)

11=11

(100)

0=3(0)

0=5(0)

4=5(80)

0=5(0)

0=2(0)

0=2(0)

2=2(100)

58=5(100)

4=14

(29)

4=14

(29)

11=15

(73)

6=10

(60)

1=10

(10)

5=10

(50)

6=10

(60)

12=13

(92)

—

Readyfood

(Pork)

8=8(100)

0=8(0)

0=8(0)

0=8(0)

0=8(0)

2=3(67)

3=3(100)

0=2(0)

0=2(0)

2=2(100)

0=2(0)

——

——

0=6(0)

0=6(0)

3=6(50)

1=3(33)

0=3(0)

2=3(66)

1=3(33)

3=3(100)

—

Raw

food

(Pork)

10=10

(100)0=

10(0)

0=10

(0)0=10

(0)0=

10(0)

2=2(100)

2=2(100)

0=1(0)

——

——

——

—0=

5(0)

0=5(0)

5=5(100)

4=5(80)

0=5(0)

2=5(40)

4=5(80)

5=5(100)

—

aTheisolate

contained

substitutionin

code83

.bTheisolate

contained

substitutionin

codon87.

c Thefiveciprofloxacin

resistan

tisolatescontained

asingle

pointmutationin

thegyrA

gen

e.Threeoftheisolatescontained

substitutionsin

codon83

andtw

oisolatesin

codon87.

dTheceftiofurresistan

tisolatesoriginatingfrom

apremature

born

childin

Den

markcontained

theblac

CTX-M

-14gen

e.eIsolatedfrom

both

freshmeat,an

imal

feed

anddeceasedan

imal.

f Oneisolatesfrom

apremature

childin

Den

markaccountedforresistan

ceto

AMP,CEF,POD,XNL,CHL,SPE,STR,SMX,TET,TMP.

gTravel

histories

wereav

ailable

for9=23

Dan

ishpatients.Molecu

larch

aracterizationwas

perform

edonResistant(R)an

dInterm

ediate

(I)isolates.

AMP,am

picillin;CEF,cefalothin;POD,cefpodoxim

e;XNL,ceftiofur;CHL,ch

loramphen

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ectinomycin;STR,streptomycin;XNL,ceftiofur;CHL,ch

loramphen

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ectinomycin;

STR,streptomycin;SMX,su

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TMP,trim

ettoprim.

fromDenmark; two isolates (2%) from importedpig or pork products; four isolates (4%) frompatients in Thailand; two isolates (2%) from rawfood; and two isolates (2%) from ready-to-eat

food. With the exception of one isolate (1%) ob-tained from Spanish pork products, antimicro-bial resistance within this cluster was limited totetracycline.

FIG. 1. Dendrographic analysis of the representative XbaI pulsed-field gel electrophoresis patterns of SalmonellaRissen isolates from Denmark and Thailand.


FIG

.2.

Den

drographic

analysisofSalmonella

Rissenpulsed

-fieldgel

electrophoresiscluster

TEEX01.0017.dkfollowingdigestionwithBlnI.

A similarity of approximately 82% wasobserved among PFGE cluster 1 strains. Thiscluster of isolates originated from Denmark andwas pan-susceptible.

In PFGE cluster 6; the predominant pattern,TEEX01.0026.DK was shared by six isolates(5%): four from Thai patients (4%), one isolate(1%) from ready-to-eat food and one isolate (1%)from a Danish patient with a history of travel toThailand prior to the infection. All of the isolates(5%) were resistant to AMP, CHL, NEO, SPE,STR, SMX, TET, and TMP (data not shown)(Fig. 1).

Discussion

The majority of Salmonella Rissen isolates in-cluded in this study exhibited resistance to tet-racycline and displayed limited resistance toother antimicrobials. A previous study fromThailand found almost all porcine isolates to befully resistant to TET, STR, and SMX (Angkiti-trakul et al., 2005). Thai isolates and isolates fromDanish patients with a history of travel to Thai-land were more likely to be resistant to AMP,CHL, STR, SMX, and TMP than isolates origi-nating from Denmark.

Almost all ampicillin-resistant isolates con-tained a sequence similar to blaTEM-1b. blaTEMgenes have also been widely found among Sal-monella isolates in other studies (Gallardo et al.,1999; Olesen et al., 2004). Chloramphenicol re-sistance was mediated by the catA1 or the cmlAgene, which has also been observed previously(Guerra et al., 2002; Zhao et al., 2007), but is alsowidespread among other gram-negative bacte-ria. Florfenicol resistance is normally encodedbythe flogene,which specifies nonenzymatic cross-resistance to both florfenicol and chloramphen-icol. However, none of the florfenicol-resistantisolates tested contained the flo gene. It has pre-viously been suggested that several of isolatesmay possess an unknown chromosomal flo gene(White et al., 2000). Tetracycline resistance wasprimarily mediated by tetA. However, the tetBgene was identified in one turkey isolate andthree of the eight Danish pig or pork isolates.tetA is commonly found on transposons such asTn1721, this gene has been identified in manygram-negative bacteria including Salmonella(Frech and Schwarz, 2000).

Sulphonamide resistance in Enterobacteriaceaeis typicallymediated by the resistance genes sulI(encoded on aClass I integron), sul2 (encodedona nonconjugative plasmid), or sul3 (putativelyassociated with both an integron system anda conjugative plasmid) (Radstrom et al., 1991).sul1-, sul2-, and sul3-mediated resistance wasidentified among the sulphamethoxazole-resistant isolates.The aph(3’’)-II gene was identified in all

neomycin-resistant isolates. This gene has pre-viouslybeen identified in several other species ofgram-negative bacteria. Streptomycin resistancewas encoded by aadA, strA, and strB. This ge-notype is also commonly observed in Denmarkamong streptomycin-resistant isolates of Salmo-nella Typhimurium (Madsen et al., 2000).Seven ciprofloxacin-resistant isolates con-

tained a single mutation in gyrA at codons 83(Ser?Phe) or 87 (Asp?Asn). Mutations atthese positions, located within the quinoloneresistance–determining region of gyrA, havebeen associated with ciprofloxacin resistance inseveral bacterial species, including high-levelciprofloxacin resistance in Salmonella spp. (Chiuet al., 2002; Casin et al., 2003; Ling et al., 2003).To our knowledge, this is the first study uti-

lizing PFGE to demonstrate the molecular di-versity of Salmonella Rissen. This appears to be agenetically diverse serotype, with 112 strainsproducing a total of 63 unique XbaI pat-terns (Fig. 1). The predominant pattern wasTEEX01.0017.DK which consisted of 22 isolatesandwas shared betweenThai patients, ready-to-eat food, raw food, Danish patients with andwithout a history of travel, and imported andDanish pig or pork. Several other patterns wereshared by isolates from different sources whichcould support a link between the reservoirs.The biological analysis strongly suggests that

Thai patients acquire Salmonella Rissen infec-tions by consumption of Thai-produced pig orpork products. These data also suggest that tra-vel to Thailand and consumption of importedand Danish-produced pig or pork products arepotential risk factors for infection with Salmo-nella Rissen infection among Danish patients.Previous studies have also indicated that Danishpatientsmight acquire infectionswith Salmonellaserotypes Corvallis or Schwarzengrund fromThailand through a combination of travelling


and the import of different food products(Archambault et al. 2006; Aarestrup et al. 2007).Source attribution analysis in Denmark has alsoshown the increased importance of importedfoodproducts as a source ofSalmonella infections(Hald et al., 2007). With increases in tourism andinternational trade, Salmonella subtypes whichhad been confined to specific regions mayemerge elsewhere. These studies emphasise theneed to view Salmonella epidemiology from aglobal perspective.

It should be noted that some degree ofselection and statistical bias may have influ-enced the results of the present study. The ma-jority of Thai isolates were collected betweenMay and June 2004 and only isolates collectedduring this time period were selected for mo-lecular characterization. In contrast, the Danishisolates were collected over a period of severalyears. Comparing isolates from different timeperiods may reduce the chances of findingclones with identical antibiogrammes or indis-tinguishable PFGE patterns. Additionally, thelimited number of isolates included in the studymight have influenced the statistical analysis ofspecific risk factors, particularly the consump-tion of imported pork. It should also be notedthat travel histories could only be obtained fornine of the 23 Danish patients. No informationregarding travel prior infectionwas available for14 patients.

Conclusion

This study suggest that travel to Thailand andthe consumption of pig or pork products (Dan-ish and imported)were risk factors forSalmonellaRissen infections among the Danish patients in-cluded in this study. This study also suggeststhat the Thai patients included in this studymostlikely became infected with Salmonella Rissen bythe consumption of Thai pig or pork products.This studymayhavepotential benefits for futureSalmonella Rissen investigations and outbreakdetection.

Acknowledgments

We are grateful to Miss Berith Kummerfeldt(NFI) for outstanding technical assistance, Dr.MikoleitMatthew (CDC,USA) for reviewing the

manuscript and improving the English, Mrs.Gitte Sørensen (NFI) for assistance in obtaininginformation on food products imported toDenmark, and Dr. Katharina E.P. Olsen andMrs. Ingrid B. Jensen (SSI) for providing strainsand data for infections in patients in Denmark.This work and hosting Mr. Si Wook Song weresupported by the World Health Organiza-tion Global Salm-Surv (http:==www.who.int=salmsurv).

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Address reprint requests to:Rene S. Hendriksen

National Food InstituteBulowsvej 27

DK-1790 Copenhagen VDenmark



�

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Article IV

Emergence of multidrug-resistant Salmonella Concord infections in Europe and the

United States in children adopted from Ethiopia, 2003-2007

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Pediatr Infect Dis J. 2009 Sep; 28 (9): 814-818.

AR

TIC

LE

IV

ORIGINAL STUDIES

Emergence of Multidrug-Resistant Salmonella ConcordInfections in Europe and the United States in Children Adopted

From Ethiopia, 2003–2007Rene S. Hendriksen,* Matthew Mikoleit, MASCP,† Christian Kornschober, MD,‡ Regan L. Rickert, MPH,†

Susan Van Duyne, MS,† Charlotte Kjelsø, MEd,§ Henrik Hasman, PhD,* Martin Cormican, PhD,¶Dik Mevius, DVM, PhD,�** John Threlfall, PhD,†† Frederic J. Angulo, DVM, PhD,†

and Frank M. Aarestrup, DVM, PhD*

Background: Multidrug-resistant Salmonella serovar Concord infectionshave been reported from children adopted from Ethiopia. We interviewedpatients, characterized the isolates, and gathered information about adop-tions from Ethiopia to assess public health implications.Methods: Information about Salmonella Concord cases and adoptionswere provided from Austria, Denmark, England (and Wales), Ireland, theNetherlands and the United States. Patients from Denmark and the UnitedStates were interviewed to determine the orphanages of origin; orphanagesin Ethiopia were visited. Isolates were subtyped by pulsed-field gel elec-trophoresis and antimicrobial susceptibility; specific antimicrobial resis-tance genes were characterized.Results: Salmonella Concord was isolated from 78 persons from 2003 to2007. Adoption status was known for 44 patients �3 years of age; 98%were adopted from Ethiopia. The children adopted from Ethiopia werefrom several orphanages; visited orphanages had poor hygiene and sani-tation and frequent use of antimicrobial agents. The number of childrenadopted from Ethiopia in the participating countries increased 527% from221 in 2003 to 1385 in 2007. Sixty-four Salmonella Concord isolatesyielded 53 pulsed-field gel electrophoresis patterns including 6 patternswith �2 indistinguishable isolates; one isolate from an Ethiopia adoptee.Antimicrobial susceptibility was performed on 43 isolates; 81% weremultidrug-resistant (�3 agents). Multidrug-resistant isolates were fromEthiopian adoptees and were resistant to third and fourth generationcephalosporins and 14% had decreased susceptibility to ciprofloxacin.Conclusions: Improved hygiene and sanitation and more appropriate useof antimicrobial agents are needed in orphanages in Ethiopia. Culturing of

stool specimens of children adopted from Ethiopia and appropriate hygienemay prevent further disease transmission.

Key Words: Salmonella, Ethiopia, adoptees, ESBL, multi-drugresistance

(Pediatr Infect Dis J 2009;28: 814–818)

Salmonella enterica is a common cause of human gastroenteritisworldwide.1–3 Although most Salmonella infections are self-

limiting, severe infections resulting in bacteremia, meningitis, anddeath may occur. Antimicrobial agents may be life-saving insevere infections. Third generation cephalosporins and fluoro-quinolones are commonly used for the treatment of Salmonellainfections in children and adults, respectively.4,5 Infections causedby antimicrobial-resistant Salmonella are more likely to requirehospitalization, and may result in more severe outcomes.6–8

In 2007, infections caused by Salmonella serovar Concord,a rare Salmonella serotype, were reported in several countriesamong children adopted from Ethiopia; the isolates from theseinfections were resistant to numerous antimicrobial agents includ-ing third generation cephalosporins.9,10 To prevent further infec-tions, we conducted a multinational investigation, in collaborationwith the Ethiopia Ministry of Health, to determine the likelysources of the infections.

PATIENTS AND METHODS

Epidemiologic InformationPublic health institutes in Europe and the United States

which identified human Salmonella Concord infections in 2003 to2007 were invited to participate in the study. Participating coun-tries sent isolates to the National Food Institute (DTU-Food) inDenmark and provided information about patients including those�3 years of age. Adoption status and country of origin wereprovided if available. Patients, or parents of patients �18 years ofage, in Denmark and the United States were interviewed todetermine the orphanage of origin for adopted patients and if thepatient had international travel before illness onset or used anti-microbial agents before specimen collection. Information aboutadoptions from Ethiopia was sought from national agencies inparticipating countries. In collaboration with the Ethiopian Nutri-tion and Health Research Institute, orphanages in Ethiopia werevisited in February 2008.

LaboratoryIsolates were serotyped at public health laboratories and

confirmed at DTU-Food.11 Isolates were subtyped by pulsed-fieldgel electrophoresis (PFGE) at state public health laboratories in theUnited States and DTU-Food according the PulseNet protocol

Accepted for publication March 3, 2009.From the *WHO Collaborating Centre for Antimicrobial Resistance in Food-

borne Pathogens and EU Community Reference Laboratory for Antimicro-bial Resistance, National Food Institute, Technical University of Denmark,Copenhagen V, Denmark; †Centers for Disease Control and Prevention,WHO Collaborating Centre for Surveillance, Epidemiology and Control ofSalmonella and other Foodborne Diseases, Atlanta, GA; ‡Institute forMedical Microbiology and Hygiene, Graz, Austria, §Statens Serum Insti-tute, SSI, Copenhagen, Denmark; ¶National University of Ireland, Galway,Ireland; �Central Veterinary Institute of Wageningen UR, Lelystad, TheNetherlands; **Department of Infectious Diseases and Immunology, Utre-cht University, Utrecht, The Netherlands; and ††Department of Gastroin-testinal, Emerging and Zoonotic Infections, Centre for Infections, London,United Kingdom.

Supported by the World Health Organization Global Salm-Surv (available at:www.who.int/salmsurv) and grant 274–05–0117 from the Danish ResearchAgency.

Address for correspondence: Rene S. Hendriksen, National Food Institute,Technical University of Denmark, Bulowsvej 27, DK-1790 Copenhagen V,Denmark. E-mail: [email protected].

Supplemental digital content is available for this article. Direct URL citationsappear in the printed text and are provided in the HTML and PDF versionsof this article on the journal’s Web site (www.pidj.com).

Copyright © 2009 by Lippincott Williams & WilkinsISSN: 0891-3668/09/2809-0814DOI: 10.1097/INF.0b013e3181a3aeac

The Pediatric Infectious Disease Journal • Volume 28, Number 9, September 2009814 | www.pidj.com

using Xba I digestion.12 PFGE patterns were compared usingBioNumerics 4.6 (Applied Maths, Sint- Martens-Latem, Belgium).Minimum inhibitory concentrations (MICs) to 25 antimicrobialagents were determined using Sensititre microbroth dilution.13

CLSI interpretive criteria were used for amikacin, ampicillin,aztreonam, cefazolin, cefepime, cefpodoxime, ceftazidime, ceftri-axone, cefuroxime, cephalothin, chloramphenicol, ciprofloxacin,gentamicin, imipenem, nalidixic acid, sulfamethoxazole, tetracy-cline, and trimethoprim14–16; and DTU-Food-defined resistancebreakpoints were used for apramycin (�16 mg/L), ceftiofur (�4mg/L) (a third generation cephalosporin used in veterinary medi-cine), colistin (�8 mg/L), florfenicol (�16 mg/L) (a phenicol usedin veterinary medicine), neomycin (�8 mg/L), spectinomycin(�64 mg/L), and streptomycin (�16 mg/L) (http://www.crl-ar.eu/_pdf/monitoring_reports/Danmap%202006.pdf).Decreased susceptibility to ceftriaxone and ciprofloxacin was de-fined as an MIC �2 mg/L and MIC �0.125 mg/L, respectively.Resistance to �3 antimicrobial agents of different classes wasdefined as multidrug-resistant.

Multidrug-resistant strains were further characterized usinga polymerase chain reaction (PCR) assay with primers specific for8 antimicrobial resistance genes13 (Table, Supplemental DigitalContent 1, http://links.lww.com/INF/A144). PCR products werepurified (GFX PCR DNA kit Amersham Biosciences), and sub-mitted to Macrogen Inc. for sequencing. Sequence analysis andalignment was performed using Vecton NTI suite 9 (InforMax,Inc.). Resulting nucleotide sequences were compared with se-

quences obtained from GenBank (available at: http://www.lahey.org/studies/webt.html). Conjugation of selected multidrug-resis-tant isolates was performed using previously described meth-ods.17,18 Transconjugation was verified by PCR using primersspecific for blaCTX-M-15 and blaSHV-12. Plasmid analysis wasperformed on selected transconjugants and their respective donorsby S1-nuclease digestion and PFGE.

Role of Funding SourceNeither of the grants for this study had any involvement in

design, collection of isolates, analysis, interpretation of data,preparation of the article or decision where to submit the study forpublication.

RESULTSPublic health institutes in Austria, Denmark, England (and

Wales), Ireland, the Netherlands and the United States reported 78cases of laboratory-confirmed Salmonella Concord infections from2003 to 2007. In the United States, Salmonella Concord wasisolated from 48 persons; 3 in 2003, 4 in 2004, 5 in 2005, 12 in2006, and 24 in 2007. In the 5 participating European countries,Salmonella Concord was isolated 30 persons; 1 in 2003, 9 in 2004,10 in 2005, 8 in 2006 and 2 in 2007 (Fig. 1). During the studyperiod, Salmonella Concord was isolated from 12 persons inAustria, 3 in Denmark, 9 in England (and Wales), 2 in Ireland, and4 in the Netherlands. Gender were known for 67 patients; 41 (61%)were female. Age was known for 75 patients. The median age was

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FIGURE 1. Number of children adopted from Ethiopia (A) and number of reported laboratory-confirmed cases of Salmonellaserotype Concord (B) per year in participating countries in Europe* and the United States, 2003–2007. *No adoption data wereavailable for Austria. References: http://www.adoptionsnaevnet.dk/; http://travel.state.gov/family/adoption/notices/notices_473.html; http://www.adoptie.nl/; http://www.adoptionboard.ie/; http://www.dfes.gov.uk/intercountryadoption/general.shtml.

The Pediatric Infectious Disease Journal • Volume 28, Number 9, September 2009 Salmonella in Adoptees From Ethiopia

© 2009 Lippincott Williams & Wilkins www.pidj.com | 815

12 months (range: 2 months–76 years); 56 (75%) were �3 years ofage and 11 (15%) were �18 years of age. Adoption status wasknown for 44 (79%) of the patients �3 years of age; of these, 43(98%) were adopted. The patient who was �3 years of age andwas not adopted was a sibling of a child adopted from Ethiopia. All43 adopted children were from Ethiopia except for 1 child whowas adopted from an unspecified African country. Of the 43adopted children, 10 adopted children were brought to Austria and33 to the other participating countries (29 to the United States, 3 toDenmark, and 1 to England). Six (54%) patients �18 years of agewere female; of these, 2 were mothers of children adopted fromEthiopia.

We interviewed patients or parents for 31 (61%) of the 51patients in Denmark and the United States. Among the 25 inter-viewed patients �3 years of age, 24 (96%) were adopted fromEthiopia. For the children adopted from Ethiopia, the median timein one or more orphanages in Ethiopia was 3 months (range: 1–6.5months). Stool specimens which yielded Salmonella Concord fromthe children adopted from Ethiopia were collected an average of 32days following adoption (range: 2–185 days). Six (25%) of thechildren adopted from Ethiopia were asymptomatic at the time ofadoption and specimen collection; 1 asymptomatic child had astool specimen cultured because of an ill sibling, and 5 asymp-tomatic children had stool specimens cultured resulting fromrecommendations by his or her pediatrician. Eighteen (75%) of thechildren adopted from Ethiopia were symptomatic at the time ofadoption; all had diarrhea, 7 (39%) had fever; 4 (22%) had bloodydiarrhea, and 3 (17%) were hospitalized. Median duration ofillness was 11 days (range: 5–90 days). One child received anti-microbial agents after illness onset and before specimen collection.Information regarding the adoption agency in Ethiopia was re-ported for 18 (75%) of the adopted children; the children wereadopted from 8 different orphanages in Addis Abba, Ethiopia.

A total of 3419 children were adopted from Ethiopia from2003 to 2007 and brought to countries participating in this study(no adoption information was available from Austria); during this5-year period, the number of children adopted from Ethiopiaincreased 527% from 221 adoptions in 2003 to 1385 in 2007. Ofthe 2852 children adopted from Ethiopia and brought to the UnitedStates, 1987 (70%) occurred in the last 2 years. Of the 567 childrenadopted from Ethiopia and brought to 1 of the 4 Europeancountries with adoption information participating in this study, 233(41%) occurred in the last 2 years. During the study period, 188children adopted from Ethiopia were brought to Denmark, 14 toEngland (and Wales), 66 to Ireland, and 299 to the Netherlands(Fig. 1).

Two orphanages in Ethiopia from where at least 3 patientswere adopted were visited. Children at the orphanages were mostcommonly abandoned at police stations shortly after birth. Familyor medical history before arrival at the orphanage was seldomknown. Children typically stayed at the orphanages for at least 3months before being adopted or sent to another agency. Poorhygiene and sanitation was observed at the orphanages. Cases ofdehydration and diarrhea were reported among the children in theorphanages. According to physicians at the orphanages, youngchildren in the orphanages were typically treated for diarrhea withceftriaxone, gentamicin and sulfamethoxazole, or with tri-methoprim and sulfamethoxazole; older children received cipro-floxacin.

LaboratorySalmonella Concord isolates from 64 (82%) of the 78

patients were subtyped by PFGE. Fifty-three unique XbaI PFGEpatterns were observed (Fig., Supplemental Digital Content 2,http://links.lww.com/INF/A145). There were 6 PFGE patterns

with �2 indistinguishable isolates. The pattern with the mostindistinguishable isolates included those from 7 children of whichat least 5 isolates were from children adopted from Ethiopia. Eachof the remaining 5 patterns with �2 indistinguishable isolatesincluded at least 1 isolate from a child adopted from Ethiopiaincluding 1 pattern with indistinguishable isolates from a childadopted from Ethiopia and his adopted mother.

Isolates were available for antimicrobial susceptibility test-ing for 43 (55%) of the 78 patients; 8 (19%) were susceptible to allagents and 35 (81%) were multidrug-resistant. Travel history wasknown for 4 of the patients infected with pansusceptible Salmo-nella Concord. None reported associations with Ethiopia but allwere adults who traveled to Kenya before illness onset; one adultalso traveled to South Africa, Zambia, and Malawi. Travel oradoption status was known for 30 of the 35 patients infected withmultidrug-resistant isolates. All were either from or associatedwith a child adopted from Ethiopia. All multidrug-resistant isolateswere resistant to ampicillin, aztreonam, cefazolin, cefepime, cef-podoxime, ceftazidime, ceftiofur, cefuroxime, cephalothin chlor-amphenicol, streptomycin, sulfamethoxazole, and trimethoprim.All multidrug-resistant isolates also had decreased susceptibility toceftriaxone; 34 (97%) were ceftriaxone-resistant. Of the multi-drug-resistant isolates, 34 (97%) were resistant to gentamicin, 24(69%) were resistant to tetracycline, and 6 (14%) showed de-creased susceptibility to ciprofloxacin.

At least 1 isolate was available for antimicrobial suscepti-bility testing from 3 of the 6 PFGE patterns with �2 indistinguish-able isolates; each of these available isolates was multidrug-resistant and was from a child adopted from Ethiopia.

All 35 multidrug-resistant isolates harbored a blaTEM geneand blaCTX gene; sequence analysis of the PCR products showed100% identity to blaTEM-1b and blaCTX-M-15, respectively. Of themultidrug-resistant isolates, 13 (37%) also harbored the blaSHV

gene; sequence analysis revealed 100% identity to blaSHV-12. Ninemultidrug-resistant isolates were selected for conjugation studies.Five transconjugants were successfully recovered yielding thesame susceptibility pattern as the donors. After digestion with S1enzyme and PFGE, a plasmid of approximately 380 kb. wasobserved. Two isolates yielded transconjugants with less resistancethan the donors (resulted in limited resistance to ampicillin, ceph-alothin, cefpodoxime, and ceftiofur). After digestion with S1 andPFGE, a single plasmid of approximately 80 kb was observed inthese 2 isolates. PCR confirmed the presence of the genes blaCTX

and the blaSHV in all transconjugants.The 6 multidrug isolates with decreased susceptibility to

ciprofloxacin were characterized. Three isolates were indistin-guishable by PFGE and contained the plasmid mediated quinoloneresistance gene qnrB; these isolates were isolated from childrenadopted from Ethiopia and brought to the United States. Twoisolates with different PFGE patterns contained the quinoloneresistance gene qnrA gene; these isolates were isolated fromchildren adopted from Ethiopia and brought to Austria. The re-maining isolate had a single base substitution in the gyrA gene atcodon 83 (�TCC {Ser} 3 TTC {Phe}�); this isolate was from a1-year old child in the United Kingdom with an unknown adoptionhistory.

DISCUSSIONIn this multinational study, we demonstrate that multidrug-

resistant Salmonella Concord infections are common among chil-dren adopted from Ethiopia. We found that from 2003 to 2007, atleast 33 (1.0%) of the 3419 children adopted from Ethiopia andbrought to the United States and 4 European countries had alaboratory-confirmed Salmonella Concord infection. In the United

Hendriksen et al The Pediatric Infectious Disease Journal • Volume 28, Number 9, September 2009

© 2009 Lippincott Williams & Wilkins816 | www.pidj.com

States alone the number was 24 cases of 2852 (0.8%) Ethiopianadoptees. Most of these infected children were symptomatic, somewith severe symptoms. Since only a fraction of Salmonella infec-tions are laboratory-confirmed, these data suggest a remarkablyhigh incidence of Salmonella infection among children in orphan-ages in Ethiopia. It is not known how long this Salmonella strainhas been present in these orphanages, but the diversity of PFGEpatterns (no indication of temporal evolution among the patterns)among the children adopted from Ethiopia and the adoption ofinfected children from at least 8 orphanages in Ethiopia indicatesan endemic problem in Ethiopian orphanages. The increasingisolation of this strain in the United States and Europe likelyreflects that increasing frequency of adoption of children fromEthiopia. Ethiopia was the fourth most common country of originfor adoptions in Denmark and the United States in 2007 followingChina, Vietnam and South Africa in Denmark (Available at:http://www.adoptionsnaevnet.dk), and China, Guatemala and Rus-sia in the United States (Available at: http://travel.state.gov/family/adoption/stats/stats_451.html).

The highly resistant nature of the Salmonella Concordisolates from children adopted from Ethiopia makes antimicrobialtreatment difficult. Although antimicrobial agents are not neces-sary for the treatment of most Salmonella infections, antimicrobialtreatment can be life-saving in severe infections.4,5 All of theisolates from children adopted from Ethiopia were resistant to 19antimicrobial agents including all antimicrobial agents commonlyused to treat Salmonella infections in children. Furthermore, someof the isolates from children adopted from Ethiopia had decreasedsusceptibility to ciprofloxacin; treatment of such infections withfluoroquinolones is not advised because such treatment has beenassociated with treatment failures.19,20

The highly resistant isolates from children adopted fromEthiopia illuminates the need for more appropriate use of antimi-crobial agents in orphanages in Ethiopia. The empiric treatment ofchildren with diarrhea at the orphanages with a combination ofceftriaxone, gentamicin, and sulfamethoxazole is particularly wor-risome. It is not known if other countries have similar endemicSalmonella problems in orphanages but the transmission of mul-tidrug-resistant Salmonella has been reported in orphanages inother countries in Africa; in a similar study of multidrug-resistantSalmonella Babelsberg and Salmonella Enteritidis infections inFrance among children adopted from Mali, the highly resistantnature of the isolates was thought to be due to the heavy use ofantimicrobial agents in orphanages in Mali.21 Preventing furtherinfections in orphanages in Ethiopia and elsewhere should focuson improvements in hygiene and sanitation. The highly resistantnature of Salmonella Concord in the orphanages in Ethiopiademonstrates the difficulties in controlling such infections usingantimicrobial agents. Treatment of children with diarrhea shouldfocus on supportive care particularly rehydration. Antimicrobialagents should be reserved for treatment of patients at risk forserious infections or with systemic symptoms.

This study provides useful information for parents adoptingchildren from Ethiopia and perhaps elsewhere. The AmericanAcademy of Pediatrics recommends that a stool specimen becollected from all adopted children and cultured for bacterialpathogens including Salmonella.22–24 Adherence to this recom-mendation identified Salmonella. Concord infections in severalasymptomatic children adopted from Ethiopia. The utility of thisrecommendation was highlighted in this study since we identifiedseveral instances in which family members were infected withSalmonella Concord which was apparently introduced into thefamily from an adopted child. Furthermore, considering the alarm-ingly high frequency of antimicrobial resistance among the Sal-

monella Concord isolates from adopted children in this studyincluding resistance to third and fourth generation cephalosporinsand ciprofloxacin, it may be useful to test Salmonella isolatesisolated from adopted children for antimicrobial susceptibility.

ACKNOWLEDGMENTSThe authors thank Berith Kummerfeldt, Christina Svendsen,

Jacob Dyring Jensen, Vibeke Hansen, and the Zoonosis laboratory(DTU-Food) for their outstanding technical assistance. In addi-tion, the authors also like to thank Katharina E.P. Olsen andIngrid B. Jensen (SSI) for providing strains and data of infectionsin patients in Denmark.

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2. Galanis E, Lo Fo Wong DM, Patrick ME, et al. Web-based surveillance andglobal Salmonella distribution, 2000–2002. Emerg Infect Dis. 2006;12:381–388.

3. Helms M, Ethelberg S, Mølbak K; DT104 Study Group. InternationalSalmonella Typhimurium DT104 infections, 1992–2001. Emerg Infect Dis.2005;6:859–867.

4. Grohskopf LA, Huskins WC, Sinkowitz-Cochran RL, et al. Use of antimi-crobial agents in United States neonatal and pediatric intensive care pa-tients. Pediatr Infect Dis J. 2005;24:766–773.

5. Hohmann EL. Nontyphoidal salmonellosis. Clin Infect Dis. 2001;2:263–269.

6. Varma JK, Molbak K, Barrett TJ, et al. Antimicrobial-resistant nontyphoi-dal Salmonella is associated with excess bloodstream infections and hos-pitalizations. J Infect Dis. 2005;191:554–561.

7. Helms M, Simonsen J, Mølbak K. Quinolone resistance is associated withincreased risk of invasive illness or death during infection with Salmonellaserotype Typhimurium. J Infect Dis. 2004;190:1652–1654.

8. Helms M, Vastrup P, Gerner-Smidt P, et al. Excess mortality associatedwith antimicrobial drug–resistant Salmonella Typhimurium. Emerg InfectDis. 2002;8:490–495.

9. Morris D, Whelan M, Corbett-Feeney G, et al. First report of extended-spectrum-beta-lactamase-producing Salmonella enterica isolates in Ireland.Antimicrob Agents Chemother. 2006;50:1608–1609.

10. Cattoir V, Weill FX, Poirel L, et al. Prevalence of qnr genes in Salmonellain France. J Antimicrob Chemother. 2007;59:751–754.

11. Popoff MY, Le Minor L. Antigenic Formulas of the Salmonella Serovars.8th ed. Paris, France: WHO Collaborating Centre for Reference andResearch on Salmonella, Institute Pasteur; 2001.

12. Ribot EM, Fair MA, Gautom R, et al. Standardization of pulsed-field gelelectrophoresis protocols for the subtyping of Escherichia coli O157:H7, Salmonella, and Shigella for PulseNet. Foodborne Pathog Dis.2006;3:59 – 67.

13. Hendriksen RS, Bangtrakulnonth A, Pulsrikarn C, et al. Antimicrobialresistance and molecular epidemiology of Salmonella Rissen from animals,food products and patients in Thailand and Denmark. Foodborne PathogDis. 2008;5:605–619.

14. Clinical and Laboratory Standards Institute. Methods for Dilution Antimi-crobial Susceptibility Tests for Bacteria That Grow Aerobically. 7th ed.Wayne, PA: Clinical and Laboratory Standards Institute; 2006. ApprovedStandard M07-A7.

15. Clinical and Laboratory Standards Institute. Performance Standards forAntimicrobial Susceptibility Testing, 18th Informational Supplement.Wayne, PA: Clinical and Laboratory Standards Institute; 2008. M100-S16.

16. Clinical Laboratory Standards Institute. Performance Standards for Anti-microbial Disk and Dilution Susceptibility Tests for Bacteria Isolated FromAnimals. 3rd ed. Wayne, PA: Clinical and Laboratory Standards Institute;2008. Approved Standard M31-A3.

17. Rice R, Bonomo RA. Genetic and biochemical mechanism of bacterial resis-tance to antimicrobial agents. In: Lorian V, ed. Antibiotics in LaboratoryMedicine. 4th ed. Baltimore, MD: Williams and Wilkins; 1996:453–501.

18. Olsen JE, Brown DJ, Thomsen LE, et al. Differences in the carriage and theability to utilize the serotype associated virulence plasmid in strains of Salmo-nella enterica serotype Typhimurium investigated by use of a self-transferablevirulence plasmid, pOG669. Microb Pathog. 2004;36:337–347.

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19. Aarestrup FM, Wiuff C, Mølbak K, et al. Is it time to change fluoroquin-olone breakpoints for Salmonella spp? Antimicrob Agents Chemother.2003;2:827–829.

20. Crump JA, Kretsinger K, Gay K, et al. Clinical response and outcome ofinfection with Salmonella enterica serotype Typhi with decreased suscep-tibility to fluoroquinolones: a United States foodnet multicenter retrospec-tive cohort study. Antimicrob Agents Chemother. 2008;4:1278–1284.

21. Weill FX, Demartin M, Tande D, et al. SHV-12-like extended-spectrum-beta-lactamase-producing strains of Salmonella enterica serotypes Babels-

berg and Enteritidis isolated in France among infants adopted from Mali.J Clin Microbiol. 2004;42:2432–2437.

22. Hostetter MK, Iverson S, Thomas W, et al. Medical evaluation of interna-tionally adopted children. N Engl J Med. 1991;325:479–485.

23. Nicholson AJ, Francis BM, Mulholland EK, et al. Health screening ofinternational adoptees: evaluation of a hospital based clinic. Med J Aust.1992;156:377–379.

24. Stauffer WM, Kamat D, Walker PF. Screening of international immigrants,refugees, and adoptees. Prim Care. 2002;29:879–905.

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Article V

Molecular characterization of extended spectrum cephalosporinases (ESC) producing

Salmonella Choleraesuis from patients in Thailand and Denmark

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Submitted to Journal of Clinical Microbiology

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Molecular characterization of extended spectrum cephalosporinases (ESC) producing ��

Choleraesuis from patients in Thailand and Denmark

Pantip Sirichote2, Henrik Hasman1, Chaiwat Pulsrikarn3, Henrik Carl Schønheyder4, Jurgita

Samulioniené4, Srirat Pornruangwong 3, Aroon Bangtrakulnonth5, Frank M. Aarestrup1, Rene S.

Hendriksen1*

1 WHO Collaborating Center for Antimicrobial Resistance in Food borne Pathogens and EU

Community Reference Laboratory for Antimicrobial Resistance, National Food Institute,

Technical University of Denmark, Bülowsvej 27, DK-1790 Copenhagen V, Denmark

2 Regional Medical Sciences Center Samutsongkhram, Department of Medical Sciences, Ministry

of Public Health, Samutsongkhram, Thailand.

3 WHO National �� and �� Center, National Institute of Health, Department of

Medical Sciences, Ministry of Public Health, Bangkok, Thailand

4 Aalborg Hospital, Aarhus University Hospital, Department of Clinical Microbiology, Aalborg,

Denmark.

5 Regional Medical Science Center Khonkaen, Department of Medical Sciences, Ministry of

Public Health, Khonkaen, Thailand.

*Corresponding author: Rene S. Hendriksen,

National Food Institute, Technical University of Denmark

Bülowsvej 27, DK-1790 Copenhagen V, Denmark

Phone: +45 72 34 60 00

1

Fax: +45 72 34 60 01


Running title: Extended spectrum cephalosporinases (ESC) producing Salmonella Choleraesuis

in Thailand and Denmark

Key words: ��Choleraesuis, bacteremia, extended spectrum cephalosporinases,

antimicrobial resistance, PFGE.

2

ABSTRACT

The objective of this study was to characterize extended spectrum cephalosporinases (ESC)

producing isolates of ��serovar Choleraesuis recovered from patients in Thailand and

Denmark.

Twenty-four isolates were included in the study, 13 of which were blood culture isolates.

Twenty-three isolates were recovered from Thai patients in 2003, 2007, or 2008 and one isolate

was recovered from a Danish traveller to Thailand. ESC production was confirmed by minimum

inhibitory concentration testing. Micro-array and plasmid profiling (replicon typing and RFLP)

were used to characterize the genetic mechanisms of antimicrobial resistance in the ESC

producing isolates. PFGE was used to compare isolates resistant to third generation

cephalosporins with susceptible isolates from Thailand during the same period.

MIC determination, micro-array, PCR, plasmid profiling and replicon typing revealed the

presence of multi-drug resistant isolates harboring either ��CMY-2 containing incA/C or ��CTX-M-

14 containing incFIIA / incFrepB located on plasmids ranging in size from 75–200 kb. The RFLP

and replicon typing clustered the isolates into four distinct groups. PFGE revealed 16 unique

patterns and five clusters; each cluster contained two to three isolates. The isolate from the

Danish patient was indistinguishable from two Thai clinical isolates.

This study revealed the emergence of the ��CTX-M-14 gene among several clones of ��

serovar Choleraesuis. Numerous plasmids were identified containing up to two different ESC

genes and four distinct replicons. A “travel associated” spread was confirmed. The findings

represent a serious threat to public health for the Thai people and tourists.

3

INTRODUCTION

�� is a common cause of human gastroenteritis and bacteremia worldwide (15,

29) and a wide variety of animals, particularly food animals, has been identified as reservoirs for

non-Typhi �� (11, 19, 20). Although approximately 2,600 serovars of ��

�� have been identified, most human infections are caused by a limited number of serovars

and in general these infections are self-limiting. Some �� serovars including �

�� Choleraesuis (swine) and �� Dublin (cattle) which are adapted to a specific

animal hosts, have a propensity to cause extra-intestinal infections in humans. When compared

to other serovars of non-Typhi ��, infections with these serovars are associated with

higher rates of bacteremia, meningitis, and mortality (4, 5, 21). For patients with severe

salmonellosis, antimicrobial chemotherapy may be life-saving. Due to increasing prevalence of

fluorquionolone resistance third generation cephalosporins are increasingly used for the treatment

of �� infections in humans (14, 18, 22) and these compounds have been designated as

critically important for human health by the World Health Organization (10).

We recently reported that human infections with ��serovar�Choleraesuis in Thailand

increased from 1.5% in 1993 to 9.2% in 2007 (16). The group of people at highest risk for these

infections was those between 6–40 years of age in the Central region of Thailand (16). A 2007

study of ��serovar�Choleraesuis isolates from Thailand observed an increasing

resistance to both third generation cephalosporins and fluoroquinolones. Fifty-four isolates

obtained between 2003 and 2005 were tested, of which 30% were found to be resistant to third

generation cephalosporins (22).

4

To date, only two reports, both from Taiwan, have described mechanisms for third generation

cephalosporin resistance in �� serovar�Choleraesuis. The first report was published in

2004 with the discovery of ��CMY-2 AmpC �-lactamase gene located on a 140 kb F-like plasmid

(6). The following year, the same authors detected ��CTX-M-3 in a �� serovar�

Choleraesuis� isolate from a patient admitted to a university hospital (28). In 2007, a massive

increase of flouroquinolone and ceftriaxone resistant �� serovar� Choleraesuis was

described in Thailand (22).

In Taiwan, the usage of antimicrobials in veterinary medicine and as growth promoter in animal

feed may have promoted the emerging of the resistance (5). Likewise, in Thailand, the third

generation cephalosporin ceftiofur is used extensively in the swine production (22).

The objectives of the present study were to determine the genetic diversity and antimicrobial

resistance of extended spectrum cephalosporinases (ESC) producing �� serovar�

Choleraesuis� isolates from patients in Thailand and Denmark. Additionally, isolates of

�� serovar� Choleraesuis from Thailand which were resistant to third generation

cephalosporins were compared with susceptible isolates using PFGE.

METHODS

0��

A total of 24 isolates were included in this study. Twenty-three isolates were recovered in

Thailand and one ESC producing isolate was recovered in 2008 at Aalborg Hospital, Aarhus

University Hospital, Denmark. The WHO National �� and ��Center in Bangkok

receives all presumptive isolates of ��spp. from all diagnostic laboratories throughout

Thailand. In 2003, as part of another study, the National Food Institute, Technical University of

5

Denmark (DTU-Food) received 82 isolates of ��serovar�Choleraesuis which were

recovered from Thai patients. (1). In 2008, this collection was screened for the presence of ESC

producing isolates and two ESC producing strains, both isolated in 2003, were identified. DTU-

Food received 12 isolates of ��serovar�Choleraesuis in 2008, ten isolates were ESC

producers isolated in 2008 from Thai patients at the Regional Medical Sciences Center in

Samutsongkhram, Thailand.

In addition, to assess the genetic diversity of ��serovar�Choleraesuis in Thailand, nine

isolates from Thailand which were susceptible to third generation cephalosporins were included

in the study. These susceptible isolates were isolated from patients in Bangkok and were

randomly selected from the collection.

��

The isolates were serotyped using slide agglutination in the country of origin.

O and H antigens were characterized by agglutination with hyperimmune sera (S & A reagents

lab, Ltd, Bangkok, Thailand and Statens Serum Institute, Copenhagen, Denmark) and serotype

was assigned according to the Kauffmann-White scheme (13).

��

Minimum inhibitory concentration testing of the 13 ESC producing isolates was performed at the

DTU-Food using previously described methods (17). Results were primarily interpreted using

current European Committee on Antimicrobial Susceptibility Testing (EUCAST)

(www.eucast.org) and European Food Safety Authority (EFSA) epidemiologic break points (26).

Due to the absence of some break points in the EUCAST system, exceptions were made for the

interpretation of cefepime and ceftriaxone where Clinical and Laboratory Standards Institute

6

guidelines and clinical breakpoints were utilised (7, 8, 9). Quality control using '�� ATCC

25922 was conducted according to CLSI.

%��

Detection of gene-groups associated with the antimicrobial resistance phenotypes was carried out

using miniaturized microarrays (Identibac Amr-ve Array tubes, New Haw, Addlestore, Surrey,

UK) containing probes for most relevant Gram-negative antimicrobial gene groups (Identibac).

Analysis was performed as described by the manufacturer on the 13 ESC producing isolates.

�

/� �� 5 ��

PCR amplification and sequencing of the ��CTX-M-9 group, ��TEM and ��CMY-2 genes were

performed on the 13 isolates using methods described previously (17, 25).

Amplicons produced were selected for sequencing. Prior to sequencing, the amplicons were

purified using the GFX™ PCR DNA kit (GE Healthcare, Chalfont St. Giles, UK) following the

protocol of the manufacturer. The DNA was shipped to Macrogen Inc., Seoul, Korea for

sequencing using the same primers as in the PCR analysis. Sequence analysis and alignment was

performed using Vecton NTI suite 9 (InforMax Inc., Bethesda, Maryland, US) software. The

resulting nucleotide sequences were compared to sequences obtained from the GenBank database

(http://www.lahey.org/studies/webt.html).

�� (� ��

Plasmid DNA was extracted using QIAGEN Plasmid Mini Kit (Qiagen, Hilden, Germany). The

plasmid DNA was transferred into electrocompetent '��DH10B cells and subjected to S1

nuclease PFGE as described below to ensure that only one plasmid had been transferred into the

7

competent cells as well as to estimate the approximate size of the plasmids carrying the ESC

phenotype. The electroporation was followed by selection of transformants on BHI agar

supplemented with cefotaxime (2 �g/ml). The presence of the plasmid in the transformants was

confirmed by PCR detection of relevant �� genes as described above. Additionally, testing was

performed to determine if any non-ESC resistance determinants co-transferred with the ESC

plasmids. The 13 transformants were analysed by PCR for all relevant resistance genes based on

the results of the Array tube analysis described above. Transformants were further subjected to

replicon PCR and plasmid purification followed by RFLP.

;��

Plasmids within transformants were replicon typed as described previously (2).

�� G��

Plate-mating experiments were performed with transformants as donors and plasmid-free,

rifampicin and nalidixic acid resistant '�� MT102RN as recipients (2, 25). The strains were

grown to both late exponential as well as stationary phase, mixed (1:1) and incubated on solid

blood agar at 37�C for 18 h. Transconjugants were selected on BHI medium supplemented with

50 �g/ml rifampicin, 32 �g/ml nalidixic acid, and 2 �g/ml cefotaxime.

�*�� (��

PFGE with S1 nuclease (Promega) digestion of whole genomic DNA performed as described

below was used to estimate sizes of larger plasmids. Following pre-incubation for 10 min. in 1:10

diluted S1 buffer, 2 mm slices of PFGE plugs made from cultures with an OD620 of 0.6 were

8

digested with 5 U of S1 (Promega, Madison, US) for 45 min. at 37�C. The slices were post-

incubated on ice for 10 min in 200 μL of ice-cold TE-buffer (10:1), loaded on the gel and run on

a CHEF-DRIII device (Bio-Rad, Hercules, USA) with a pulse time of 6.8 s – 38.4 s at 6 V/cm for

19 h. ��Braenderup H9812 digested with &��I was used as size marker .

�

��

All 24 isolates included this study were analyzed for genetic relatedness by PFGE using &��I

according to the CDC PulseNet protocol (24). The electrophoresis was performed with a CHEF

DR III System (Bio-Rad Laboratories, Hercules, CA, USA) using 1% SeaKem agarose in 0.5×

Tris-borate-EDTA at 180 V. Running conditions consisted of one pulse time of 2.2 - 63.8 s for 22

h at 6 V/cm on a 120 deg. angle in 14°C TBE buffer. Comparison of the PFGE profiles was

performed by using Bionumerics software version 4.6 (Applied Maths, Sint-Martens-Latem,

Belgium) and the dice correlation for band matching with a 0.9 % position tolerance and an

optimization at 0.9 % using both &�� .

RESULTS

'��

Twelve of the ESC producing isolates from Thai patients were obtained from blood samples;11

of the isolates were obtained in Ratchaburi Province and one was from Bangkok. The 12 isolates

were obtained from 10 patients with two patients each having two positive blood cultures. All

samples were collected between April and May or between August and October. The patients

were unevenly distributed by gender, with eight isolates obtained from males and two from

females. The age of one patient was unknown. However, the age of the remaining nine patients

9

ranged from 17 to 58 years with a median of 34 years. Data on occupation of the patients were

not collected.

'�� /��

A healthy 37-year old Danish male was on assignment to an industrial company in Bangkok from

July 27 to August 14 in 2008. He resided in a five star international hotel at Sukhumvit Road in

the center of Bangkok and worked full time at the Navanakorn Industrial Estate Zone 3 situated

45 km outside of Bangkok. Meals were primarily served in the hotel and at the work place.

Typical Thai food (soup and rice dishes) was daily consumed and included either fish or minced

pork.

One week before the return to Denmark the patient contracted diarrhoea with an acute onset, but

without blood. The patient was febrile up to 38.8°C with dizziness, cephalgia, and mild muscle

pain. Concurrently, the patient noticed flexor paresis of the interphalangeal joint of the left thumb

accompanied by hypestesia in the C6 dermatome. Except for paresis and hypestesia the

symptoms abated in a few days and the diarrhoea responded to loperamide. However, symptoms

recurred several times and the patient was admitted to a Danish hospital on September 10th with a

weight loss of 11 kg. A blood culture obtained by admission revealed ��serovar�

Choleraesuis. Fecal cultures during admission were negative.

Empirical antimicrobial treatment included ciprofloxacin and pivmecillinam. Treatment with

meropenem was considered based on the multi-drug resistant phenotype of the isolate, but the

patient felt well and he declined. Eight months later the patient was in good health though the

flexor paresis persisted.

�

��

10

All of the 13 ESC producing isolates were multi-drug resistant and exhibited resistance to at least

13 of the tested antimicrobials (eight antimicrobial drug classes) (Figure 1). Resistance was not

detected to apramycin (only approved for veterinary use), colistin, imipenem, meropenem and

trimethoprim. All isolates were resistant to ampicillin, cefalothin, cefazolin, cefotaxime,

cefpodoxime, ceftiofur, nalidixic acid, sulphamethoxazole and tetracycline. Twelve isolates

(92%) were resistant to chloramphenicol; four (31%) of these strains also were resistant to

florfenicol (only approved for veterinary use). Resistance to ciprofloxacin was observed in twelve

(92%) isolates, one isolate had a MIC just below the break point of ciprofloxacin. Eleven (85%),

four (31%), four (31%), and four (31%) of the isolates were resistant to the ceftriaxone,

ceftazidime, cefepime, and cefoxitin, respectively (Figure 1). Four isolates (31%) were also

resistant to amoxicillin and clavulanic acid and another six isolates (46%) to gentamicin. Only

two isolates (15%) were resistant to neomycin whereas eleven (85%) and ten (77%) isolates were

resistant to spectinomycin and streptomycin, respectively.

��

Based on Array tube analysis and subsequent sequencing of PCR-generated DNA fragments,

eight of the 13 ESC producing isolates harbored the extended spectrum � -lactamase gen group

��CTX – M-9, the chloramphenicol resistance acetyltransferase gen ��A, the sulphonamide

resistance gen ��3, the aminoglycoside resistance gen ��A1, and the tetracycline resistance gen

� B. In addition, five (SH2867/08, SH2868/08, SH2871/08, SH2872/08, 08-120226) of the eight

isolates also harbored the intergase gen � 1.

Of the remaining five isolates, four contained the ��R gen conferring resistance to florfenicol, the

sulphonamide resistance gen ��2, the intergase gen � 1 encoding an intergron, the

aminoglycoside resistance genes � �A and � �B, the plasmidic ampC gen ��CMY, and the

11

tetracycline gen � A. In addition, one (SH508/03) of the four isolates also harbored the � B and

��1 genes. Furthermore, three (SH2870/08, SH2874/08, SH508/03) of the four isolates contained

also the aminoglycoside resistance gen ��A1.

One isolate (SH1208/03) was resistant to sulphamethoxazole and tetracycline containing the ��1

and � B genes, respectively. In addition, this isolate harbored the extended spectrum � -

lactamase gen group ��CTX – M-9 and the ��TEM gen.

The isolates which produced amplicons to ��CTX – M-9 group, ��CMY and ��TEM were sequenced

and showed 100% similarity to strains in the Genbank encoding for ��CTX-M-14 , ��CMY-2 and�

��TEM-1b, respectively.

�� (� ��*��)>'�� ;)C��

Approximate plasmid sizes were given in Figure 2 and ranged from approximately 75 kb to 200

kb. Plasmid profiling by RFLP separated the plasmids into three distinct clusters (I, II and III in

Figure 2). Furthermore, one plasmid profile (from strain SH1208/03) was not associated to any of

the three main groups. The plasmid with ��CMY-2 genes was associated to cluster I, while

plasmids harboring the ��CTX-M-14 gene belonged to the two remaining clusters as well as the

plasmid out of line with the three clusters (Figure 2). Replicon typing identified the incA/C

replicon in RFLP cluster I, the incFrep in cluster II and incFIIA in cluster III, while the plasmid

from SH1208/03 was untypable.

$�� '�$��

The PCR results revealed that only one (SH2862/08) of the eight ESC producing isolates which

harbored the extended spectrum �-lactamase gen group ��CTX – M-14 successfully transferred non-

12

ESC resistance determinants. In addition to ��CTX – M-14, the transformant contained the ��3, the

��A1 and the � B genes.

The four transformants containing plasmid ampC gen ��CMY-2 seemed to harbor many of the

non-ESC resistance determinants. All of the four transformants contained the ��R, the ��2, the

� �A / � �B and � A genes. In addition, one (SH508/03) of the four transformants also contained

the ��1 gene and three transformants (SH2870/08, SH2874/08, SH508/03) contained the ��A1

gene.

The transformant of the one isolate (SH1208/03) which harbored the ��CTX – M-14 also contained

the ��TEM gen.

�

$��G�� 5��

By conjugation experiments we found the ESC phenotype readily transferable from wild type

strains carrying plasmids belonging to RFLP cluster I and cluster II as well as from isolate SH

1208/03. However, the four strains carrying the incFIIA type plasmids of RFLP cluster III did not

succeed.

�

�)>'� ��

The 24 �� serovar� Choleraesuis isolates from 22 patients were subtyped by PFGE.

Sixteen unique &��I PFGE patterns were observed (Figure 1). There were five distinct PFGE

clusters with >2 indistinguishable isolates. Three clusters contained ESC producing isolates of

which two included two indistinguishable isolates from different Thai patients (SH2858/08,

SH2867/08 and SH2870/08, SH2874/08). A second cluster contained three isolates with

indistinguishable patterns, two isolates from one Thai patient (SH2871-08, SH2872-08) (different

susceptibility profiles) and the isolate (08-120226) from the Danish traveller to Thailand. The

13

two remaining clusters only contained isolates susceptible to third generation cephalosporins of

which one included isolates from both 2003 and 2008.�

DISCUSSION

This study provides the first description of��CTX-M-14 in ��serovar Choleraesuis isolates

and is the first reported isolation of an ESC producing �� serovar Choleraesuis in an

international traveller who recovered with sequelae from his infection. In addition, these data

provide evidence that ESC producing isolates have emerged in Thailand on several plasmids and

in several clusters of ��Choleraesuis.

Characterization of the antimicrobial resistance genes indicates some similarity between isolates

harboring either ��CTX-M-14 or ��CMY-2. The data from the plasmid characterization, conjugation,

replicon typing and RFLP also suggested that these are not highly clonal strains and further

grouped the isolates into four distinct replicon clusters. Based on the data of the unknown

replicon, one could speculate if the plasmid of isolate SH1208/03 was the ancestor to the other

isolates harboring the ��CTX-M-14 gene and simply evolved rather than spread to other strains. All

of the analyses indicate multiple clones and multiple plasmids being responsible for the

resistance to extended spectrum cephalosporinases producing �� serovar Choleraesuis

obtained from patients in Thailand and Denmark.

Several studies have described plasmids carrying ��CMY-2 containing the incA/C replicon along

with other resistance genes. A recent Canadian study investigated 38 '�� isolates where all of

the isolates harbored a plasmid carrying ��CMY-2 containing the incA/C replicon (24). A similar

association between ��CTX-M14 and incFII has been described previously. Geraldine Marcade � �

�� found that the great majority of genes encoding ��CTX-M-14 and ��CTX-M-15 were carried by

14

IncF replicons. Of 15 '�� isolates harboring ��CTX-M-14 eight of them contained the replicon

IncFII (23,.

PFGE patterns revealed a high degree of clonal diversity among the 24 isolates. ESC producing

and non-ESC producing isolates were generally interspersed although some rare clusters

comprised solely resistant or susceptible isolates. This indicates that multiple clones are

circulating in the population and that isolates resistant to third generation cephalosporins most

likely developed due to a long standing selection pressure from the use of these compounds in a

veterinary reservoir rather than a recent spread of a single clone.

�� serovar Choleraesuis has been eradicated from the primary production of swine in

Denmark and many other industrialised countries. The isolate from the Danish traveller shared

the an identical PFGE pattern with an isolate from a Thai patient infected in the autumn of 2008.

The isolates were resistant to the same antimicrobials and harbored the same resistance genes

with exception of two additional resistance traits in the isolate from the Danish patient, namely

resistance to amoxicillin + clavulanic acid and gentamicin. We have no explanation for this

discrepancy because the Danish patient did receive only symptomic therapy prior to admission to

the hospital in Denmark.

The Danish case was remarkable for neurologic symptoms localized to the left hand which

coincided with diarrhoeal illness and persisting for at least 9 months. There was no evidence of

focal infection, but the similarity with mononeuropathy in association with typhoid fever may

indicate a common pathogenesis (12).

15

Thailand is a popular tourist destination for Europeans. Thus, in 2008 149.570 Danes visited

Thailand (http://www.tourism.go.th/). During the same year, 3,022 confirmed cases of

�� infections in humans were reported to Statens Serum Institute, Denmark. Of these,

706 (23.3%) were confirmed as travel associated and 95 (13.4%) cases were linked to travelling

to Thailand (Data not published). These numbers might be underestimated and probably should

be multiplied with 10 -20 times (30). Taking this underestimation into consideration 0.6% of the

Danes visiting Thailand might bring back a �� infection based on these data.

The infections with ��serovar Choleraesuis�has recently increased in Thailand and the

emergence of ESC producing �� serovar Choleraesuis makes this problem even more

serious (16). We therefore urge the Thai authorities to take action in order to prevent and control

the spread of this serovar among animals and the human population. Targeted interventions can

benefit swine farmers by reducing losses and possible export restrictions. These interventions can

also reduce the high costs of hospitalization associated with treatment of invasive ��

serovar Choleraesuis infections which include the necessity to use carbapenems which are

antibiotics of last resort. We recommend enforcing a strict policy on the usage of antimicrobials

in food animals and a ban on the usage of third generation cephalosporins as growth promoter.

CONCLUSSION

This study provides for the first time a description of�� CTX-M-14 found in �� serovar

Choleraesuis isolates and documents a case of bacteremia with an ESC producing ��

serovar Choleraesuis acquired by a Danish traveller during a stay in Bangkok. The data suggest

that ESC producing isolates have emerged in Thailand on several plasmids and in multiple clones

of ��serovar Choleraesuis.

16

We found two genes and four replicons responsible for the resistance to third and fourth

generation cephalosporins present in the isolates from both 2003 and 2008. In addition, the

isolates exhibit a huge diversity among the molecular patterns indicating a variable population

despite having similar resistance patterns and genes.

The Thai authorities should initiate immediate actions to control and prevent infections with this

invasive serovar for the benefit of the Thai people and tourists travelling to Thailand. The first

step could be specific serovar targeted intervention and limitations in the usage of third

generation cephalosporins as growth promoters in the primary production of pigs.

ACKNOWLEDGEMENTS

We are grateful to Mrs. Christina Aaby Svendsen and Miss. Lisbeth Andersen (National Food

Institute) for outstanding technical assistance, to Dr. Matthew Mikoleit (Centers for Disease

Control and Prevention, US) for reviewing the manuscript and improving the English, and to Dr.

Steen Ethelberg (Statens Serum Institute, Denmark) for providing data on travel associated

infections in Danish patients.

This work was supported by the World Health Organization Global Salm-Surv

(www.who.int/salmsurv).

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23

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Article VI

Risk factors and epidemiology of the ten most common Salmonella serovars from

patients in Thailand; 2002 - 2007.

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AR

TIC

LE

VI

Original Article

Risk Factors and Epidemiology of the Ten Most CommonSalmonella Serovars from Patients in Thailand: 2002–2007

Rene S. Hendriksen,1 Aroon Bangtrakulnonth,2 Chaiwat Pulsrikarn,2 Srirat Pornruangwong,2

Gorrawan Noppornphan,2 Hanne-Dorthe Emborg,1 and Frank M. Aarestrup1

Abstract

We conducted a retrospective observational study to assess epidemiological trends and risk factors associatedwith the 10 most common Salmonella serovars isolated from humans in Thailand between 2002 and 2007. A totalof 11,656 Salmonella isolates covering all 6 years were included in the study. The top 10 Salmonella serovarsidentified during the course of this study were Enteritidis, Stanley, Weltevreden, Rissen, I [1],4,[5],12:i:�,Choleraesuis, Anatum, Typhimurium, Corvallis, and Panama, which accounted for 8108 (69.6%) of the isolates.Most isolates were from patients <5 years (33%), were isolated during June (13%), and were recovered from stool(82%) and from patients in Bangkok (27%). Statistical analysis revealed that S. Enteritidis and S. Choleraesuiswere recovered from blood with a higher frequency than other nontyphoidal serovars. While both serovarstended to be isolated from patients >5 years; S. Choleraesuis was recovered with a higher frequency frompatients in Bangkok and the central region, whereas S. Enteritidis was recovered predominantly from patients inthe southern region. This study also indicates a shift in prevalence of the most common Salmonella serovarsresponsible for human infections in Thailand compared to previous studies. Notably, there was an increase inhuman infections with S. Stanley, S. Corvallis, and S. Choleraesuis, three serovars that have previously beenassociated with swine, and a decrease in infections due to S. Weltevreden and S. Anatum. The study alsorevealed differences in the epidemiology among the different serovars, suggesting that serovar-specific inter-ventions are needed. We recommend initiating targeted interventions for the two serovars associated with a highodds ratio for submitted blood samples, S. Enteritidis and S. Choleraesuis. The authors also recommend addi-tional epidemiologic studies to investigate the observed increase in swine associated serovars (S. Stanley, S.Corvallis,and S. Choleraesuis) and determine interventions to reduce the burden of disease from these serovars.

Introduction

Salmonella enterica is a common cause of humangastroenteritis and bacteremia and a wide variety of ani-

mals, particularly food animals, have been identified asreservoirs for nontyphoidal Salmonella (Coyle et al., 1988;Humphrey et al., 1988; Humphrey, 2000). A limited number ofthe 2579 currently recognized serovars of Salmonella accountfor the vast majority of human infections. In developedcountries, S. Typhimurium and S. Enteritidis are the mostcommon causes of human salmonellosis, but other serovarshave been reported to be more prevalent in specific regions(Humphrey, 2000; Herikstad et al., 2002; Aarestrup et al., 2003;Bangtrakulnonth et al., 2004; Galanis et al., 2006).

Knowledge of the prevalence and epidemiology of differ-ent serovars in specific regions may facilitate the recognitionand control of new and emerging pathogens. Previous studieshave shown that Salmonella serovars Choleraesuis, Dublin,Virchow, Enteritidis, and Panama tend to cause invasivedisease and are associated with higher mortality rates. Thesestudies have reported mortality rates of 1.8% and 3.0% forS. Choleraesuis and S. Dublin, respectively, compared with0.5% for all nontyphoidal Salmonella and 0.6% for S. Typhi-murium (Helms et al., 2002; Chiu et al., 2004; Jones et al., 2008).The explanations for this observed increased virulence have notbeen fully elucidated and are most likely multifactoral.

The following retrospective observational cross-sectionalstudy was conducted to elucidate the epidemiological trends

1World Health Organization (WHO) Collaborating Centre for Antimicrobial Resistance in Foodborne Pathogens and EU CommunityReference Laboratory for Antimicrobial Resistance, National Food Institute, Technical University of Denmark, Copenhagen, Denmark.

2WHO International Salmonella and Shigella Centre, National Institute of Health, Department of Medical Sciences, Ministry of PublicHealth, Thailand.

FOODBORNE PATHOGENS AND DISEASEVolume 6, Number 8, 2009ª Mary Ann Liebert, Inc.DOI: 10.1089=fpd.2008.0245

1009

of the 10 most common Salmonella serovars isolated fromhumans in Thailand between 2002 and 2007. Additionally, ananalysis of risk factors for human salmonellosis in Thailandwas performed. Risk factor analysis for infection with 1 of the10 most common nontyphoidal Salmonella serovars wascompared to other nontyphoidal Salmonella serovars in thestudy. Salmonella serovars Typhi, Paratyphi A, and ParatyphiB were not included in the study based on the relatively lowprevalence in Thailand (2.1%) (Annual Report of ConfirmedSalmonella and Shigella in Thailand, 2006). The followingvariables were included in the analysis: age group, season,sex, specimen type, and geographical region.

The results of this study provide insight into the epidemi-ology and the specific factors responsible for human salmo-nellosis among patients in Thailand. These data may assistwith targeted interventions to control infections by invasiveSalmonella serovars.

Methods

Data source

The World Health Organization (WHO) National Salmo-nella and Shigella Centre in Bangkok receives all presumptiveisolates of Salmonella from all public health laboratories inThailand. Confirmatory identification is performed at theWHONational Salmonella and ShigellaCentre using approvedinternationally recognized procedures. Following confirma-tion, isolates are serotyped by slide agglutination as previ-ously described (Bangtrakulnonth et al., 2004).

For each isolate, the following clinical and epidemiologicaldata are electronically recorded in Microsoft Excel 2000spreadsheets (Microsoft Corporation, Redmond, WA): jour-nal number, laboratory number, date, given name, surname,sex, age including age group, origin, geographical zone, ori-gin of sample, specimen, serogroup, and serotype. There is noindication in the data source if only one or more samples havebeen submitted per patient.

Data set

The data set contained of a total of 11,656 Salmonella isolateswith complete information covering the years from 2002 to2007 (Table 1). The dependent variables were the 10 mostcommon serovars in Thailand. Odds ratio of being infectedwith each of the 10 serovars were calculated as being infectedwith serovar number 1 compared to the rest of the serovars inthe data set, the odds ratio of being infected with serovarnumber 2 compared to the rest of the serovars in the dataset, etc.

The qualitative variables—age group, season, and region—were aggregated into fewer levels due to the number of de-grees of freedom, which caused problems when running thealgorithm. Originally, age groups were given in intervals of 5years but were aggregated into only five levels: 0–5, 6–20, 21–40, 41–60 and >60 years. Similarly, season and regions wereaggregated from months into four seasonal periods (winter,spring, summer, and autumn) and from 13 zones into fiveregions (central, northeast, southern, northern, and Bangkok).Many of the strains were isolated from various parts of thebody and from various materials, thus only specimens origi-nating from blood and fecal samples (rectal swabs or stool)were included in the analysis (Table 1).

Statistical analysis

The statistical package SAS version 9.1.3 (SAS InstituteInc., Cary, NC) was used to perform the logistic analysis. Apreselection of independent variables was initiated usingunivariable analysis and all independent variables with ap-value of <0.05 was included in logistic analysis. A fullmodel was fitted for each serotype including all independentvariables. Backward selection was performed using p-values.The criteria for keeping variables in the model was p-values<0.05. The full model and the reduced model were com-pared using the log likelihood ratio test to test the contri-bution of the independent variables in the final model. Thefinal models contained several different independent vari-ables. To understand the meaning of the models, the oddsratio of being infected with 1 of the 10 most common serovarscompared to the remaining other nontyphoidal Salmonellaserovars was calculated for each level of the independentvariables (Tables 2 and 3). Biological meaningful two-factorinteractions were not analyzed as they were beyond the scopeof this article.

Results

Descriptive data

A total of 11,656 isolates collected from Thai patients withsalmonellosis between 2002 and 2007 were included in thisstudy. The 10 most common Salmonella serovars in this studywere S. Enteritidis (n¼ 1517 [13%]); S. Stanley (n¼ 1292[11%]); S. Weltevreden (n¼ 1055 [9%]); S. Rissen (n¼ 969[8%]); S. I [1],4,[5],12:i:� (n¼ 690 [6%]); S. Choleraesuis(n¼ 681 [6%]); S. Anatum (n¼ 551 [5%]); S. Typhimurium(n¼ 540 isolates [5%]); S. Corvallis (n¼ 476 isolates [4%]); andS. Panama (n¼ 337 isolates [3%]), which accounted for 8108(69.6%) of the isolates (Table 1). We have not received anyinformation to suggest that these data are biased or dispro-portionate due to the occurrence of a local or regional out-break.

The proportion of the nontyphoidal Salmonella serovarsdecreased from 49.6% (n¼ 1629) in 1993 to 24.4% (n¼ 1981) in2007. The proportion of S. Anatum, which peaked at 10.1%(n¼ 412) in 2000, decreased to 0.3% (n¼ 7) in 2006. Similarly,by 2006, the proportion of S. Weltevreden, had decreased 13years in a row to 7.3% (n¼ 151) and continued to decline in2007, representing 6.6% (n¼ 130) of cases. During this sameperiod, increases in S. Choleraesuis were observed. The pro-portion of S. Choleraesuis isolates increased from 2.8%(n¼ 55) in 2002 to 9.2% (n¼ 190) in 2006. This study alsoretrospectively identified the emergence in 2003 of S. Cor-vallis, a serovar not recorded in Thailand since 1993. From2003 to 2007, the level of S.Corvallis remained fairly constant,representing approximately 4.5% (n¼ 45) of cases. The pro-portion of S. Rissen remained relatively constant from 1997 to2004, ranging from 5.9% (n¼ 46) of cases in 1998 to 9.6%(n¼ 81) of cases in 2004. The proportion of S. Panama de-creased in 2002 from 6.7% (n¼ 130) of cases to 2.4% (n¼ 33) ofcases in 2003 and remained at this level through 2007. Theproportion of S. Stanley increased since 1993 (1.9%; n¼ 64) toa maximum level in 2003 (10.1%; n¼ 141). While decreases inthe proportions of S. Enteritidis and S. I [1],4,[5],12:i:� wereobserved in 2004 and 2005 compared to previous years, sub-sequent increases were observed in 2007 with S. Enteritidis


Table1.

DescriptiveDataoftheVariableandLevelsUsedforAnalyzingtheSignificantFactorsCausingInfections

AmongThaiPatientswith

theTop10

MostCommonSalmonellaSerovarsin

2002–2007

Variables

Levels

Overall

N(%

)

S.

Enteritidis

N(%

)

S.

Stanley

N(%

)

S.

Weltevreden

N(%

)

S.

Rissen

N(%

)

S.

I[1],4,[5],12:i:�

N(%

)

S.

Choleraesuis

N(%

)

S.

Anatum

N(%

)

S.

Typhim

urium

N(%

)

S.

Corvallis

N(%

)

S.

Panam

aN

(%)

Others

N(%

)

Agegroup

(years)

0–5

3830

(32.9)

210(13.8)

664(51.4)

274(26.0)

368(38.0)

265(38.4)

78(11.5)

119(21.6)

188(34.8)

175(36.8)

184(54.6)

1305

(36.8)

6–20

1283

(11.0)

134(10.4)

131(10.2)

171(13.3)

101(7.9)

44(3.4)

54(4.2)

75(5.85)

53(4.1)

56(4.4)

27(2.1)

437(34.1)

21–40

3021

(25.9)

636(21.1)

174(5.8)

237(7.9)

222(7.4)

208(6.9)

329(10.9)

168(5.6)

134(4.4)

94(3.1)

51(1.7)

768(25.4)

41–60

1871

(16.1)

302(19.9)

156(12.1)

185(17.4)

145(15.0)

106(15.4)

124(18.2)

99(18.0)

91(16.9)

71(14.9)

39(11.6)

553(15.6)

>60

1651

(14.2)

235(15.5)

167(12.9)

188(17.8)

133(13.7)

67(9.7)

96(14.1)

90(16.3)

74(13.7)

80(16.8)

36(10.7)

485(13.7)

Season

Winter

(Dec.–Feb

.)25

51(21.9)

379(25.0)

305(23.6)

236(22.4)

234(24.2)

147(21.3)

152(22.3)

124(22.5)

100(18.5)

86(18.1)

71(21.1)

717(20.2)

Spring

(Mar.–May

)28

71(24.6)

334(22.0)

322(24.9)

232(22.0)

229(23.6)

233(33.8)

172(25.3)

114(20.7)

148(27.4)

129(27.1)

118(35.0)

840(23.7)

Summer

(Jun.–Aug.)

3485

(29.9)

423(27.9)

358(27.7)

343(32.5)

299(30.9)

154(22.3)

159(23.4)

204(37.0)

180(33.3)

140(29.4)

94(27.9)

1130

(31.9)

Autumn

(Sep

.–Nov.)

2750

(23.6)

381(25.1)

307(23.8)

244(23.1)

207(21.4)

156(22.6)

198(29.1)

109(19.8)

112(20.7)

121(25.4)

54(16.0)

861(24.3)

Sex

Fem

ale

5591

(48.0)

680(44.8)

608(47.1)

565(53.6)

486(50.2)

295(42.8)

267(39.2)

295(53.5)

272(50.4)

237(49.8)

154(45.7)

1732

(48.8)

Male

6065

(52.0)

837(55.2)

684(52.9)

490(46.5)

483(49.9)

395(57.3)

414(60.8)

256(46.5)

268(49.6)

239(50.2)

183(54.3)

1816

(51.2)

Specim

enFeces

(stool,

rectal

swab

)95

78(82.2)

594(39.2)

1254

(97.1)

1037

(98.3)

954(98.5)

496(71.9)

86(12.6)

546(99.1)

426(78.9)

458(96.2)

313(92.9)

3414

(96.2)

Blood

2078

(17.8)

923(60.8)

38(2.9)

18(1.7)

15(1.6)

194(28.1)

595(87.4)

5(0.9)

114(21.1)

18(3.8)

24(7.1)

134(3.8)

Reg

ion

Cen

tral

(zone1,

2,3,

4)40

57(34.8)

484(31.9)

411(31.8)

345(32.7)

314(32.4)

197(28.6)

463(68.0)

203(36.8)

152(28.2)

192(40.3)

127(37.7)

1169

(33.0)

Northeast

(zone5,

6,7)

1228

(10.5)

146(9.6)

172(13.3)

124(11.8)

94(9.7)

64(9.3)

32(4.7)

78(14.2)

39(7.2)

28(5.9)

19(5.6)

432(12.2)

Southern

(zone11

,12

)14

50(12.4)

277(18.3)

112(8.7)

267(25.3)

65(6.7)

89(12.9)

11(1.6)

25(4.5)

94(17.4)

42(8.8)

29(8.6)

439(12.4)

Northern

(zone8,

9,10

)18

02(15.5)

299(19.7)

181(14.0)

156(14.8)

164(16.9)

145(21.0)

72(10.6)

86(15.6)

103(19.1)

66(13.9)

33(9.8)

497(14.0)

Ban

gkok

(zone13

)31

19(26.8)

311(20.5)

416(32.2)

163(15.5)

332(34.3)

195(28.3)

103(15.1)

159(28.9)

152(28.2)

148(31.1)

129(38.3)

1011

(28.5)

OverallN

1165

615

1712

9210

5596

969

068

155

154

047

633

735

48

Table2.

MultivariableAnalysisoftheSignificantSingleFactorsin

theTop10

NontyphoidalSalmonellaSerovars

CausingSalmonellosisAmongtheThaiPatientsComparedtoOtherNontyphoidalSalmonellaSerovars

S.Enteritidis

S.Stanley

S.Weltevreden

S.Rissen

S.I[1],4,[5],12:i:�

Variables

Levels

OR

OR

(95%

CI)

p-value

(LR)

OR

OR

(95%

CI)

p-value

(LR)

OR

OR

(95%

CI)

p-value

(LR)

OR

OR

(95%

CI)

p-value

(LR)

OR

OR

(95%

CI)

p-value

(LR)

Agegroup(years)

<0.0001

<0.0001

<0.0001

<0.0001

0–5

1.00

1.00

1.00

1.00

6–20

1.58

1.24–2.02

0.56

0.46–0.69

1.91

1.55–2.35

0.44

0.32–0.61

21–40

2.18

1.81–2.61

0.37

0.31–0.44

1.40

1.16–1.69

0.78

0.64–0.96

41–60

1.86

1.51–2.29

0.50

0.42–0.61

1.67

1.36–2.04

0.67

0.53–0.86

>60

1.79

1.44–2.21

0.60

0.50–0.72

1.86

1.52–2.27

0.49

0.37–0.65

Reg

ion

<0.0001

<0.0001

<0.0001

<0.0001

<0.0001

Ban

gkok

1.00

1.00

1.00

1.00

1.00

Cen

tral

0.83

0.70–0.99

0.90

0.78–1.05

1.71

1.40–2.08

0.77

0.65–0.91

0.77

0.62–0.94

Northeastern

1.11

0.91–1.35

1.05

0.87–1.28

1.75

1.38–2.20

0.97

0.80–1.19

1.33

1.05–1.67

Northern

1.11

0.88–1.41

1.36

1.11–1.66

1.78

1.39–2.28

0.69

0.54–0.88

0.97

0.72–1.30

Southern

2.45

2.01–3.00

0.61

0.49–0.76

3.87

3.14–4.77

0.39

0.30–0.51

1.10

0.84–1.43

Specim

en<0.0001

<0.0001

<0.0001

<0.0001

<0.0001

Feces

1.00

1.00

1.00

1.00

1.00

Blood

11.12

9.77–12.66

0.16

0.12–0.22

0.07

0.04–0.11

0.06

0.04–0.11

2.01

1.67–2.43

Season

0.0027

0.0027

Summer

1.00

1.00

Spring

0.89

0.75–1.06

1.84

1.49–2.28

Autumn

1.12

0.95–1.33

1.25

0.99–1.58

Winter

1.22

1.03–1.45

1.26

1.00–1.60

Table3.

MultivariableAnalysisoftheSignificantSingleFactorsin

theTop10

NontyphoidalSalmonellaSerovars

CausingSalmonellosisAmongtheThaiPatientsComparedtoOtherNontyphoidalSalmonellaSerovars

S.Choleraesuis

S.Anatum

S.Typhim

urium

S.Corvallis

S.Panam

a

Variables

Levels

OR

OR

(95%

CI)

p-value

(LR)

OR

OR

(95%

CI)

p-value

(LR)

OR

OR

(95%

CI)

p-value

(LR)

OR

OR

(95%

CI)

p-value

(LR)

OR

OR

(95%

CI)

p-value

(LR)

Agegroup

(years)

0.0140

<0.0001

<0.0001

0–5

1.00

1.00

1.00

6–20

1.63

1.08–2.46

2.19

1.62–2.96

0.50

0.33–0.75

21–40

1.51

1.12–2.04

2.62

2.04–3.35

0.44

0.32–0.61

41–60

1.14

0.81–1.60

2.19

1.66–2.90

0.52

0.36–0.75

>60

1.17

0.82–1.67

2.16

1.62–2.87

0.53

0.37–0.77

Reg

ion

<0.0001

<0.0001

<0.0001

<0.0001

0.0001

Ban

gkok

1.00

1.00

1.00

1.00

1.00

Cen

tral

3.29

2.57–4.22

0.93

0.74–1.15

0.75

0.59–0.94

1.08

0.86–1.34

0.88

0.68–1.14

Northeastern

0.60

0.43–0.84

0.87

0.66–1.15

1.15

0.89–1.49

0.86

0.64–1.16

0.58

0.39–0.86

Northern

0.77

0.50–1.20

0.97

0.73–1.29

0.64

0.45–0.91

0.47

0.31–0.70

0.46

0.28–0.76

Southern

0.19

0.10–0.36

0.26

0.17–0.40

1.35

1.04–1.77

0.60

0.42–0.85

0.51

0.34–0.77

Specim

en<0.0001

<0.0001

0.0381

<0.0001

<0.0001

Feces

1.00

1.00

1.00

1.00

1.00

Blood

44.00

34.28–56.47

0.03

0.01–0.08

1.26

1.01–1.56

0.17

0.10–0.27

0.45

0.29–0.70

Season

0.0074

0.0004

<0.0001

Summer

1.00

1.00

1.00

Spring

1.14

0.87–1.48

0.66

0.52–0.84

1.53

1.16–2.02

Autumn

1.43

1.10–1.85

0.64

0.50–0.81

0.71

0.50–1.00

Winter

0.93

0.71–1.22

0.83

0.65–1.04

1.02

0.74–1.40

and S. I [1],4,[5],12:i:� comprising 16.0% (n¼ 316) and 4.5%(n¼ 90), of the cases for 2007, respectively (Fig. 1).

Age distribution

The patients’ ages ranged from 1 day to 96 years. The ma-jority of infections (n¼ 640, 32.6%) were observed in patientsbetween 0 and 5 years (Fig. 1). The frequency of infectionsamong the patients rapidly decreased after the fifth year of lifeto an average annual level of 3.2–4.4% (n¼ 63–86) among pa-tients from 6 to 20 years. A higher frequency of infection wasalso observed among patients in the second and third decadesof life. This age group on average represented 144 cases (7.5%)per year. The frequency of infection plateaued through thesixth decade to an average of 60 cases per year (3.1%) at age 60.The frequency of infection peaked for the third time amongpatients older than 60 years. This age group accounted for anaverage of 280 cases (14.0%) per year (Table 1, Fig. 2).

Sex

No differences were observed based on patients’ sex. Overthe 6-year period, 52.1% of patients were female and 47.9%were male.

Seasonal trends

Infections peaked in June with an average of 1456 cases(12.5%). Overall, the fewest cases (n¼ 745) were reportedduring the month of April. However, S. I [1],4,[5],12:i:�peaked in April with an average 113 cases compared to 65cases in June (Table 1, Fig. 3).

Specimen source

The majority of isolates (82.2%) were recovered from stoolor rectal swabs whereas the remaining 17.8% of samples wererecovered from blood. Between 2002 and 2005, the percentageof isolates recovered from blood decreased from 15.2% in 2002to 8.4% in 2005. However, the percentage of blood isolatesmore than doubled in 2006 to 29.3% and remained relativelyunchanged (25.2%) in 2007.

Regional variation

The majority (n¼ 3119) of infections were reported from theBangkok region (Table 1). The 10 most common serovars de-scribed in this study were present in Bangkok; however, theproportion of S. Enteritidis was the lowest (10%) when com-pared to the other four regions (Fig. 4). A large number of cases(n¼ 4057) were also reported in the central region. Similar toBangkok, all of the serovars described in the study were pres-ent in the central region. In addition, the central region had thehighest proportion of S. Choleraesuis (11%), which ranked asthe sixth most common serovar in that region (Fig. 4).

A large number of infections were also observed in thenorthern region, specifically within zones 8 and 10. SalmonellaKedougou accounted for 5% of the cases in the northern re-gion. In contrast to other regions, S. Panama was not listedamong the 10 most commonly reported serovars, having beensurpassed by S. Kedougou.

The southern region, which includes both the eastern andthe western peninsulas, accounted for the greatest number ofsalmonellosis cases due to S. Enteritidis (19%) and S. Wel-

tevreden (18%) compared to the other regions. A small per-centage of cases in the southern region were due to swine-associated serovars: S. Stanley (8%), S. Rissen (4%), and S.Corvallis (3%). S. Choleraesuis was not among the 10 mostcommonly reported serovars in the southern region. How-ever, in contrast to other regions, SalmonellaAlbany accountedfor 3% of cases and was ranked as the 10th most commonserovar in the southern region (Fig. 4).

Only 1228 cases were observed in the northeastern region(zones 5, 6, and 7) and were atypical in comparison with theother regions because neither S.Choleraesuis, S.Corvallis, norS. Panama were among the top 10 most common serovars(Table 1). These serovars were displaced by S. Hvittingfoss(6%), S. Derby (4%), and S. Virchow (3%) which rankedeighth, ninth, and tenth, respectively, among the top 10 mostcommon serovars in the region (Fig. 4).

Risk factors

Blood invasive Salmonella serovars. The statistical anal-ysis revealed that S. Enteritidis, S. Choleraesuis, and to alesser extent S. I [1],4,[5],12:i:� and S. Typhimurium wererecovered from blood at a significantly increased odds ratiowhen compared to other nontyphoidal Salmonella serovars.The highest odds ratio for isolation of S. Choleraesuis orS. Enteritidis from blood was observed among patients olderthan 5 years, whereas with S. I [1],4,[5],12:i:� the highest oddsratio was observed among patients younger than 6 years.S. Typhimurium was isolated from blood with a higher oddsratio in the southern region (zones 1, 2, 3, and 4); however, agedid not appear to be a significant predisposing factor forS. Typhimurium infection.

Seasonal variations were observed among several serovars.The odds ratio for infection with S. Choleraesuis appeared tobe higher during autumn (Tables 2 and 3, Fig. 3), whileS. Enteritidis cases peaked in winter and S. I [1],4,[5],12:i:�cases increased in spring. Odds ratios for infection withS. Enteritidis and S. I [1],4,[5],12:i:� typically declined duringthe summer. S. Anatum cases typically increased duringsummer with a lower odds ratio in the remaining part of theyear (Tables 2 and 3, Fig. 3).

In comparison to the other regions, the highest odds ratiofor S. Choleraesuis infection was observed among patientsin Bangkok and the central region. Patients in Bangkok andthe central region also had the lowest odds ratio of S. I [1],4,[5],12:i:� infections. The highest odds ratio of infection withS. Enteritidis was identified in the southern region. Thenortheastern region had the lowest rate of S. Panama andS. Corvallis infections (Table 2, Fig. 4).

Diarrhea-associatedSalmonella serovars. Themost com-mon Salmonella serovars associated with gastrointestinalinfections in Thai patients were S. Stanley, S. Weltevreden, S.Rissen, S. Anatum, and S. Corvallis (Table 2). The majority ofS. Stanley infections were among patients between 0 and 5years while S.Weltevreden and S.Anatum primarily infectedpatients older than 5 years. S. Panama showed a clear asso-ciation with patients between 0 and 5 years and was typicallyrecovered from stool samples.

Geographic trends were also observed among these ser-ovars. S. Weltevreden cases were reported predominantlyfrom the southern region and the majority of S. Rissencases were reported from the northern region and Bangkok


0%

20%

40%

60%

80%

100%

1993

*

1994

*

1995

*

1996

*

1997

*

1998

*

1999

*

2000

*

2001

*20

0220

0320

0420

0520

0620

07

Years

Cas

es i

n p

erce

nta

ges

S. Weltevreden

S. Typhimurium

S. Stanley

S. Rissen

S. Panama

S. I [1],4,[5],12:i:-

S. Enteritidis

S. Corvallis

S. Choleraesuis

S. Anatum

Others

FIG. 1. Distribution of the top 10 nontyphoidal Salmonella serovars among Thai patients from 1993 to 2007. The top 10nontyphoidal Salmonella serovars as used in the logistic regression analysis. The chart legend lists the different serotypes onthe right, which are represented in sequential order in the chart. The percentage of cases for each serovar is represented by thedifference in thickness. *Data include all clinical Salmonella isolates.

0,0

5,0

10,0

15,0

20,0

25,0

30,0

35,0

0-5

6-10

11-1

5

16-2

0

21-2

5

26-3

0

31-3

5

36-4

0

41-4

5

46-5

0

51-5

5

56-6

0

>60

Age groups

Cas

es in

per

cen

tag

es

FIG. 2. Distribution of age among Thai patients with salmonellosis from 2002 to 2007.

0

200

400

600

800

1000

1200

1400

1600

Janu

ary

Febru

ary

Mar

chApr

ilM

ayJu

ne July

Augus

t

Septe

mbe

r

Octobe

r

Novem

ber

Decem

ber

Months

no

. of

case

s

S.Enteritidis

S.Stanley

S.Weltevreden

S.Rissen

S I.[1],4,[5],12:i:-

S.Choleraesuis

S.Anatum

S.Typhimurium

S.Corvallis

S.Panama

Others

FIG. 3. Seasonal variation of Salmonella cases from Thai patients between 2002 and 2007. The chart legend lists the differentserotypes on the right, which are represented in sequential order in the chart. The percentage of cases for each serovar isrepresented by the difference in thickness. The top 10 nontyphoidal Salmonella serovars as used in the logistic regression analysis.

(Table 2, Fig. 4). The majority of S. Rissen cases reported overthe course of the study were from the northern region; how-ever, the majority of cases from the northeastern region weredue to S. Stanley (Table 2 and Fig. 4).

Discussion

Occurrence

When compared to previously published studies showingthe prevalence from 1993 to 2002, the data in this study sug-gest a shift in the prevalence of the top 10 nontyphoidal ser-ovars associated with human salmonellosis in Thailandbetween 2002 and 2007 (Bangtrakulnonth et al., 2004).

Our data indicate that while rates of S. Weltevreden, S.Derby, S.Agona, and S.Anatum are decreasing, S. Stanley, S.Choleraesuis, and S. Corvallis are increasing. Although theincreases in S. Corvallis and S. Stanley are notable, the in-creased occurrence of more invasive serovars such as S.Choleraesuis is more worrisome. This increase is particularlyconcerning amid recent reports of S. Choleraesuis strains re-

sistant to fluoroquinolone and extended-spectrum cephalo-sporin. A recent study of 56 S. Choleraesuis isolates reportedapproximately 60% of the study isolates to be nalidixic acidresistant and 15% to be ceftriaxone resistant (Kulwichit et al.,2007). These reports emphasize the importance of initiatingactions to control the spread of this serovar.

The marked decrease in S. Weltevreden has made S. En-teritidis the most common serovar associated with humaninfections in Thailand. These data contradict a publicationthat forecasted a decline in the occurrence of S. Enteritidis(Bangtrakulnonth et al., 2004). Interestingly, another studyfrom 2006 failed to find any S. Enteritidis in humans from thenorthern region (Padungtod and Kaneene, 2006).

Previous studies have described possible reservoirs inThailand for many of the serovars described in this study( Jerngklinchan and Saitanu, 1993; Sakai and Chalermchaikit,1996; Sasipreeyajan et al., 1996; Bangtrakulnonth et al., 2004;Vaeteewootacharn et al., 2005; Ponce et al., 2008).

Most studies in Thailand have associated S. Rissen, S. Cor-vallis, S. I 1, 4, 5, 12:i:�, S. Stanley, S. Choleraesuis, and

FIG. 4. Distribution of the top 10 most common serovars in the different regions in Thailand from 2002 to 2007. Thenumbers on the pie charts correspond with the numbered serovars in the chart legend to the right of the figure. Color versionof this figure is available online at www.liebertonline.com.


S. Typhimurium with swine and pork products. In 2004, 295S. Rissen isolates originating from various food sources inThailand were investigated and the majority (n¼ 220) of theisolates originated frompork products (Hendriksen et al., 2008).These results were supported by a study of swine performed inThailand in 2008; 49% of the tested swine harbored S. Rissen.Additionally, 19% and 12% of the animals also harbored S.Typhimurium and S. Stanley, respectively (Dorn-In et al., 2008).

S. Corvallis has also been reported from food sources inThailand. Publications in 2006 and 2007, described a total of12 S. Corvallis isolates from food sources in Thailand (beef,n¼ 2; chickenmeat, n¼ 6; and pork, n¼ 4) (Archambault et al.,2006; Cavaco et al., 2007). The relationship between 138 iso-lates of S. Typhimurium and S. I 1, 4, 5, 12:i:� in humans andswine from Thailand has been investigated and swine havebeen postulated as a reservoir for both serovars (Pornruang-wong et al., 2008).

In contrast to the swine-related serovars, S. Enteritidis, S.Anatum, and S. Panama have been associated with chickenand poultry products in Thailand. The most predominantserovar was S. Enteritidis, which was present in 28% of retailchicken meat in Thailand (Boonmar et al., 1998a). The sameauthor has also described the spread of a S. Enteritidis cloneamong chickens and humans in Thailand (Boonmar et al.,1998b).

Other studies have also suggested that S. Panama may beassociated with swine and pork in Thailand, while S. Rissen,S. Corvallis, and S. Stanley may be associated with chicken. Across-sectional investigation of retail food in Thailand deter-mined that S.Anatumwas primarily associated with beef andpork while S.Corvallis was primarily associated with chicken(Vindigni et al., 2007).

Several studies have also shown an association between S.Weltevreden and seafood, environmental sources, or vegeta-bles. However, this serovar has also been found in both swineand chicken. Publications describe S.Weltevreden as themostcommon serovar associated with Thai frozen shrimp (Boon-mar et al., 1998c), and it was also found in 22 isolates of 48isolates recovered from chicken (Padungtod and Kaneene,2006).

Fermented food has historically been recognized as a po-tential cause of foodborne disease. Consumption of fermentedpork and seafood products is common across Thailand, andcontamination with Salmonella ssp. has previously been re-ported with Nham, a traditional Thai fermented ground-porksausage (Paukatong and Kunawasen, 2001).

Prior to this study, there have only been limited reports ofS. Choleraesuis in Thailand. Previous reports from Thailandhave shown that S. Choleraesuis was the second most com-mon cause of septicemia between 1988 and 1996 (Boonmaret al., 1998c; Chiu et al., 2004). Additionally, one article re-ported the isolation of S. Choleraesuis from 54 Thai patientsbetween 2003 and 2005 (Kulwichit et al., 2007).

This study suggests that in the northern region, humaninfections with swine-associated serovars are increasing andhuman infections with chicken-associated serovars are de-creasing. Conversely, swine-associated serovars are decreas-ing and chicken- and seafood-associated serovars areincreasing in southern Thailand. The distribution of animal-associated serovars may be cultural and could reflect reducedpork consumption and increased poultry consumptionwithina large Muslim population in southern Thailand.

Risk factors

Previously published studies have shown that S. En-teritidis, S. Typhimurium, S. Panama, and S. Choleraesuis areassociated with a higher percentage of extra-intestinal infec-tions and increased hospitalization rates (Helms et al., 2003;Jones et al., 2008). The most commonly recovered serovarsfrom blood samples in Thailand were S. Enteritidis, S. Cho-leraesuis, S. I [1],4,[5],12:i:�, and to a lesser extent S. Typhi-murium (Tables 2 and 3). Invasive S. Enteritidis infectionshave previously been reported in Thailand. Two publicationsdescribed increased morbidity associated with S. Enteritidisand reported that S. Enteritidis, followed by S. Choleraesuis,were the most common Salmonella serovars recovered fromblood (Boriraj et al., 1997; Boonmar et al., 1998c).

Our analysis indicates that patients submitting rectal swabsor stool samples had a greater risk for infection with S. Stan-ley, S. Weltevreden, S. Rissen, and S. Anatum than othernontyphoidal serovars (Tables 2 and 3). Several publicationsalso associated these serovars with gastrointestinal infections.For example, in 2003, S. Rissen and S. Stanley were the twomost common serovars recovered from Thai patients withdiarrhea (Angkititrakul et al., 2005), and S.Weltevreden and S.Anatum were the leading causes of diarrhea in 1993 to 1996(Moolasart et al., 1997).

The age distribution of the cases was not unexpected. Themajority of the cases occurred among children and olderadults. This is consistent with the general understanding ofSalmonella epidemiology (de Wit et al., 2000). We foundthat children between 0 and 5 years were at higher risk ofbeing infected with S. Stanley as compared to the other non-typhoidal Salmonella serovars (Table 2). This is in agreementwith data from a previous study in which 4 out of 15 childrenwere infected with S. Stanley (Moolasart et al., 1997; Pa-dungtod and Kaneene, 2006).

S.Anatumhas been reported as a cause of infections among38% (n¼ 32) of crop farm workers (Padungtod and Kaneene,2006). This result is also in concordance with our analysis thatshows a higher risk for S. Anatum infection among thoseolder than 6 years.

Patients older than 6 years were also at a greater risk forinfection with S. Enteritidis and S. Weltevreden. These find-ings are consistent with previous studies (Boriraj et al., 1997).As these serovars have been associated with specific reser-voirs, their association with specific age groups may reflect anindividual’s diet. S. Weltevreden for example has been asso-ciated with shrimp, a food product not commonly given tovery small children (Boonmar et al., 1998c).

Seasonal variation was observed for most cases in thesummer period (Fig. 3), which is in agreement with what hasbeen observed elsewhere in the same region (Cho et al.,2008).

The majority of cases were reported from Bangkok and thecentral region (Fig. 2). This large number of cases reportedfrom Bangkok is most likely due to a combination of popu-lation density, better reporting, and the high prevalence ofstreet vendors selling ‘‘ready to eat food.’’ The large number ofcases from zone 4 (within the central region) may simply bedue to logistics, because this area is in close geographicproximity to Bangkok and samples can easily be collected andtransported. Reasons for the high proportion of cases in thesurrounding districts are uncertain.

RISK FACTORS OF SALMONELLA IN THAILAND 1017

We expected to find more human cases in the northernregion based on previous studies where 19% of a total of 403people sampled tested positive for Salmonella ssp. among thehealthy population in the northeastern region (Vaeteewoo-tacharn et al., 2005). In another study from the northern regionthe prevalence in livestock farmers and slaughterhouseworkers was 36% and 25%, respectively (Padungtod andKaneene, 2006). It could be speculated that high prevalence isassociated with working with animals and that the generalpopulation has a much lower prevalence.

The data in this study reveal a high number of infectionscaused by nontyphoidal Salmonella serovars in Thailand,which are potentially preventable. In order to address theproblem, the responsible authorities in Thailand need to takeaction to diminish the level of this burden. It is suggested thata source attribution program be created to reveal the true linkbetween the different Salmonella serovars. The informationobtained from this attribution study can then be used to con-trol these infections by launching targeted, serovar-specificinterventions against the true reservoirs.

Limitations

The epidemiological data from Thailand were based on apassive monitoring of samples submitted to the WHO Inter-national Salmonella and Shigella Centre, National Institute ofHealth.

Throughout the course of the study, three zones (7, 9, and11) consistently reported low numbers of cases (data notshown). It is not known whether this reflects actual numbersor possible data gaps. The authors do not have specificknowledge of the capacity for clinical laboratories in thesezones to isolate Salmonella spp. nor do we have any infor-mation on the local infrastructure needed for a laboratory-based surveillance system. In addition, habits and local rou-tines may differ from one part of a country to another withregard to how often a doctor is consulted.

Conclusion

The outcome of this study indicates a shift in prevalence ofthe most common Salmonella serovars responsible for humaninfections in Thailand compared to previous studies. Swine-related serovars in Thailand such as S. Stanley, S. Corvallis,and S. Choleraesuis are increasing while S. Weltevreden andS. Anatum are decreasing. Most infections among Thai pa-tients occur in the age groups 0–5, 31–35, and >60 years. Themajority of cases are reported from Bangkok and surroundingareas with a peak in reported infections during the summermonths.

Multiple risk factors, which varied by region and serovar,were identified in this study. Based on the variability of theserisk factors, the authors recommend initiating interventionstargeted to specific serovars taking regional, age group, andseasonal variation into account. We strongly encourage theThai authorities to initiate interventions against the two maininvasive serovars, S. Enteritidis and S. Choleraesuis. Inter-ventions for S. Enteritidis should be focused on patients olderthan 5 years in the southern region and interventions forS. Choleraesuis should be directed towards people older than5 years in the central region. In addition, studies can be un-dertaken to elucidate the reasons for the increase in swine-

associated serovars and identify control methods to reducethe burden of disease associated with these organisms. Wealso suggest initiating longer term prevention and controlmeasures by exploring possibilities to collect data for sourceattribution focusing on the reservoirs contributing to salmo-nellosis among the Thai population.

Acknowledgments

We are grateful to Dr. Mikoleit Matthew (WHO Collabor-ating Centre for Surveillance, Epidemiology and Control ofSalmonella and other Foodborne Diseases, Centers for Dis-ease Control and Prevention, Atlanta, GA) for performing anoutstanding review of the final version of the manuscript andimproving the English. This work was supported by theWorld Health Organization Global Salm-Surv (www.who.int=salmsurv).

Disclosure Statement

No competing financial interests exist.

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Address correspondence to:Rene S. Hendriksen

National Food InstituteTechnical University of Denmark

Bulowsvej 27DK-1790 Copenhagen V

Denmark


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